Database Management Questions 2
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Praise for Database Design for Mere Mortals™, Second Edition
“This book takes the somewhat daunting process of database design and breaks
it into completely manageable and understandable components. Mike’s ap-
proach whilst simple is completely professional, and I can recommend this book
to any novice database designer.”
—Sandra Barker, Lecturer, University of South Australia, Australia
“Databases are a critical infrastructure technology for information systems and
today’s business. Mike Hernandez has written a literate explanation of data-
base technology—a topic that is intricate and often obscure. If you design data-
bases yourself, this book will educate you about pitfalls and show you what to
do. If you purchase products that use a database, the book explains the tech-
nology so that you can understand what the vendor is doing and assess their
products better.”
—Michael Blaha, consultant and trainer,
author of A Manager’s Guide to Database Technology
“If you told me that Mike Hernandez could improve on the first edition of Data-
base Design for Mere Mortals I wouldn’t have believed you, but he did! The sec-
ond edition is packed with more real-world examples, detailed explanations, and
even includes database-design tools on the CD-ROM! This is a must-read for
anyone who is even remotely interested in relational database design, from the
individual who is called upon occasionally to create a useful tool at work, to the
seasoned professional who wants to brush up on the fundamentals. Simply put,
if you want to do it right, read this book!”
—Matt Greer, Process Control Development, The Dow Chemical Company
“Mike’s approach to database design is totally common-sense based, yet he’s ad-
hered to all the rules of good relational database design. I use Mike’s books in
my starter database-design class, and I recommend his books to anyone who’s
interested in learning how to design databases or how to write SQL queries.”
—Michelle Poolet, President, MVDS, Inc.
From the Library of Stephen Benoit
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“Slapping together sophisticated applications with poorly designed data will
hurt you just as much now as when Mike wrote his first edition, perhaps even
more. Whether you’re just getting started developing with data or are a seasoned
pro; whether you’ve read Mike’s previous book or this is your first; whether
you’re happier letting someone else design your data or you love doing it your-
self—this is the book for you. Mike’s ability to explain these concepts in a way
that’s not only clear, but fun, continues to amaze me.”
—From the Foreword by Ken Getz, MCW Technologies,
coauthor ASP.NET Developer’s JumpStart
“The first edition of Mike Hernandez’s book Database Design for Mere Mortals
was one of the few books that survived the cut when I moved my office to
smaller quarters. The second edition expands and improves on the original in so
many ways. It is not only a good, clear read, but contains a remarkable quantity
of clear, concise thinking on a very complex subject. It’s a must for anyone inter-
ested in the subject of database design.”
—Malcolm C. Rubel, Performance Dynamics Associates
“Mike’s excellent guide to relational database design deserves a second edition.
His book is an essential tool for fledgling Microsoft Access and other desktop da-
tabase developers, as well as for client/server pros. I recommend it highly to all
my readers.”
—Roger Jennings, author of Special Edition Using Access 2002
“There are no silver bullets! Database technology has advanced dramatically,
the newest crop of database servers perform operations faster than anyone
could have imagined six years ago, but none of these technological advances will
help fix a bad database design, or capture data that you forgot to include! Data-
base Design for Mere Mortals™, Second Edition, helps you design your database
right in the first place!”
—Matt Nunn, Product Manager, SQL Server, Microsoft Corporation
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“When my brother started his professional career as a developer, I gave him
Mike’s book to help him understand database concepts and make real-world ap-
plication of database technology. When I need a refresher on the finer points of
database design, this is the book I pick up. I do not think that there is a better
testimony to the value of a book than that it gets used. For this reason I have
wholeheartedly recommended to my peers and students that they utilize this
book in their day-to-day development tasks.”
—Chris Kunicki, Senior Consultant, OfficeZealot.com
“Mike has always had an incredible knack for taking the most complex topics,
breaking them down, and explaining them so that anyone can ‘get it.’ He has
honed and polished his first very, very good edition and made it even better. If
you’re just starting out building database applications, this book is a must-read
cover to cover. Expert designers will find Mike’s approach fresh and enlightening
and a source of great material for training others.”
—John Viescas, President, Viescas Consulting, Inc., author of Running Microsoft
Access 2000 and coauthor of SQL Queries for Mere Mortals
“Whether you need to learn about relational database design in general, design
a relational database, understand relational database terminology, or learn best
practices for implementing a relational database, Database Design for Mere Mor-
tals™, Second Edition, is an indispensable book that you’ll refer to often. With
his many years of real-world experience designing relational databases, Michael
shows you how to analyze and improve existing databases, implement keys, de-
fine table relationships and business rules, and create data views, resulting in
data integrity, uniform access to data, and reduced data-entry errors.”
—Paul Cornell, Site Editor, MSDN Office Developer Center
From the Library of Stephen Benoit
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Praise for the First Edition
“[A]n astoundingly fresh approach to the ‘nasty’ task of database design . . .
Anyone who has anything to do with creating applications using a database
product should buy this book and read it cover to cover.”
—John Viescas, President, Viescas Consulting, Inc., author of Running Microsoft
Access 2000 and coauthor of SQL Queries for Mere Mortals
“[A] must-have for anyone new to relational database design . . . [Mike’s] atten-
tion to detail is marvelous, and the explanations of the interview process are a
must-read for anyone, including experienced relational database designers.”
—Jim Booth, Principal Consultant, James Booth Consulting
“Mike has done us a favor by taking an academic topic and making it logical, ap-
proachable, and comprehensible for us mortals. Anyone interested in making
their database design better should read this book. It contains good information
for every level of database developer.”
—Malcolm C. Rubel, Contributing Editor, Databased Advisor and FoxPro Advisor
“Database Design for Mere Mortals is sure to help both aspiring and practicing
database designers alike! Michael delivers the major points of logical database
design with a clear, common-sense approach that makes this book an excellent
resource and a pleasure to read.”
—Nick Evans, Contributing Editor, PowerBuilder Advisor Magazine
“No matter what specific database package you’re using (or, perhaps, no pack-
age at all), the concepts in this book will make sense, and will apply to your da-
tabase design projects.”
—From the Foreword by Ken Getz, MCW Technologies,
coauthor, ASP.NET Developer’s JumpStart
From the Library of Stephen Benoit
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Database Design for Mere Mortals™ Second Edition
From the Library of Stephen Benoit
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Addison-Wesley presents the For Mere Mortals® Series
Series Editor: Michael J. Hernandez
The goal of the For Mere Mortals® Series is to present you with information on important technology topics in an easily accessible, common-sense manner.The primary audience for Mere Mortals books is that of readers who have little or no background or formal training in the subject matter. Books in the Series avoid dwelling on the theoretical and instead take you right into the heart of the topic with a matter-of-fact,hands-on approach. The books are not designed to address all the intricacies of a given technology, but they do not avoid or gloss over complex, essential issues either. Instead, they focus on provid- ing core, foundational knowledge in a way that is easy to understand and that will prop- erly ground you in the topic.This practical approach provides you with a smooth learning curve and helps you to begin to solve your real-world problems immediately. It also pre- pares you for more advanced treatments of the subject matter, should you decide to pur- sue them,and even enables the books to serve as solid reference material for those of you with more experience.The software-independent approach taken in most books within the Series also teaches the concepts in such a way that they can be applied to whatever particular application or system you may need to use.
Titles in the Series:
Project Management for Mere Mortals®
Claudia M. Baca. ISBN: 0321423453
User Interface Design for Mere Mortals™ Eric Butow. ISBN: 0321447735
Database Design for Mere Mortals®, Second Edition: A Hands-On Guide to Relational Database Design Michael J. Hernandez. ISBN: 0201752840
Microsoft Office Project for Mere Mortals®: Solving the Mysteries of Microsoft Office Project Patti Jansen. ISBN: 0321423429
UML for Mere Mortals®
Robert A. Maksimchuk and Eric J. Naiburg. ISBN: 0321246241
VSTO for Mere Mortals™ Kathleen McGrath and Paul Stubbs. ISBN: 0321426711
SQL Queries for Mere Mortals®: A Hands-On Guide to Data Manipulation in SQL, Second Edition John L.Viescas and Michael J. Hernandez. ISBN: 0321444434
For more information, check out the series web site at www.awprofessional.com/ForMereMortalsSeries.
From the Library of Stephen Benoit
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Database Design for Mere Mortals™ Second Edition
A Hands-On Guide to Relational Database Design
Michael J. Hernandez
Boston • San Francisco • New York • Toronto • Montreal
London • Munich • Paris • Madrid
Capetown • Sydney • Tokyo • Singapore • Mexico City
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From the Library of Stephen Benoit
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Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and Addison-Wesley was aware of a trademark claim, the designations have been printed with initial capital letters or in all capitals.
The author and publisher have taken care in the preparation of this book, but make no expressed or implied warranty of any kind and assume no responsibility for errors or omissions. No liability is assumed for incidental or consequential damages in con- nection with or arising out of the use of the information or programs contained herein.
The publisher offers discounts on this book when ordered in quantity for bulk pur- chases and special sales. For more information, please contact:
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Library of Congress Cataloging-in-Publication Data
Hernandez, Michael J. (Michael James), 1955– Database design for mere mortals : a hands-on guide to relational database
design / Michael J. Hernandez—2nd ed. p. cm.
Includes bibliographic references and index. ISBN 0-201-75284-0 (alk. paper) 1. Database design. 2. Relational databases. I. Title.
QA76.9.D26 H477 2003 005.75'6—dc21 2002034545
Copyright © 2003 by Michael J. Hernandez.
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form, or by any means, electronic, mechani- cal, photocopying, recording, or otherwise, without the prior consent of the pub- lisher. Printed in the United States of America. Published simultaneously in Canada.
For information on obtaining permission for use of material from this work, please submit a written request to:
Pearson Education, Inc. Rights and Contracts Department 75 Arlington Street, Suite 300 Boston, MA 02116 Fax: (617) 848-7047
ISBN 0-201-75284-0 Text printed in the United States on recycled paper at Courier Stoughton in Stoughton, Massachusetts. 6 7 8 9 10—CRS—07060504
Printing13th February 2008
From the Library of Stephen Benoit
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For my wife, Kendra, who has always believed in me.
In loving memory of our cats, Chico and Bugs. Writing just isn’t the
same without them.
Dedicated to anyone who has unsuccessfully attempted to design
a relational database.
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About the Author
Michael J. Hernandez currently works at Microsoft as a program manager for
the Developer Tools team of the Visual
Studio .NET group. Previously, he was
an independent relational database con-
sultant specializing in relational data-
base design. Mike is a veteran database
developer with more than 14 years of ex-
perience developing applications for a
wide variety of clients in diverse indus-
tries. He has worked with several relational database management
systems throughout his career and has been working exclusively with
Access since Version 1.0 and with SQL Server since version 7.0. Mike
is coauthor of the best-selling SQL Queries for Mere Mortals and has
been a contributing author to, columnist for, and technical editor of
various database books and periodicals.
Aside from his work on various database development projects and writ-
ing projects, Mike has also been a veteran instructor for nationally rec-
ognized training organizations such as AppDev, Deep Training, and
Focal Point, Inc., and traveled across the nation teaching Microsoft Ac-
cess, SQL Server, SQL/92 query construction, and relational database
design. For more than 13 years, Mike trained thousands of students
from Fortune 500 companies, the military, the government, and the pri-
vate sector. He consistently received top ratings from his students and
became one of the premiere instructors in the country. He’s spoken at
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xii About the Author
various national and international conferences, such as the 2001 Mi-
crosoft Office Deployment and Development Conference in Orlando,
Florida, and the 2002 Microsoft Office Solutions Conference in Palm
Springs, California. Mike became deeply involved in Microsoft’s .NET ini-
tiative and was one of the first 200 Microsoft-authorized .NET instruc-
tors. He participated in Microsoft’s nationwide .NET Developers Training
Tour and in Deep Training’s .NET Training Tour in San Jose, Costa Rica.
Now he travels across the country on behalf of Microsoft.
Mike has been studying the guitar since 1967 and was actually a pro-
fessional guitarist for 15 years, playing a wide variety of styles. His abil-
ity to enthuse his audiences comes from years of entertaining, and Mike
has a reputation among his colleagues for being quite uninhibited. He’s
played the guitar for his students, subjected anyone within earshot to a
collection of the world’s worst puns, played the game Charades to illus-
trate a point, and caused minor uproars with his imitations of George
Bush, Sr., and Ross Perot.
Some of Mike’s musician friends have talked him into coming out of re-
tirement, and he is playing once again in front of gracious and apprecia-
tive audiences. He’s taken to playing a lot of Bossa Nova and finger-style
jazz and is even composing his own music. With any kind of luck, he’ll
eventually have enough material to produce his own music CD.
On those rare occasions when he has free time, Mike usually spends it
at one of three places: drinking a “Tall Americano with room” at any im-
mediately available Starbucks, hanging out in the database section at
any Barnes & Noble bookstore, or hitting golf balls at the local driving
range and pretending he is Lee Trevino.
If you’d like to contact Mike, you can e-mail him at
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xiii
Contents
Foreword xxv
Preface (Second Edition) xxix
Preface (First Edition) xxxiii
Introduction xxxvii What’s New in the Second Edition xxxix
Who Should Read This Book xli
The Purpose of This Book xlii
How to Read This Book xlv
How This Book Is Organized xlvi
Part I: Relational Database Design xlvi
Part II: The Design Process xlvi
Part III: Other Database-Design Issues xlviii
Part IV: Appendixes xlviii
A Word About the Examples and Techniques in This Book xlix
A New Approach to Learning l
PART I: RELATIONAL DATABASE DESIGN 1
Chapter 1: The Relational Database 3 Topics Covered in This Chapter 3
Types of Databases 4
Early Database Models 5
The Hierarchical Database Model 5
The Network Database Model 9
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The Relational Database Model 12
Retrieving Data 15
Advantages of a Relational Database 17
Relational Database Management Systems 18
Beyond the Relational Model 21
What the Future Holds 22
A Final Note 24
Summary 24
Review Questions 26
Chapter 2: Design Objectives 27 Topics Covered in This Chapter 27
Why Should You Be Concerned with Database Design? 27
The Importance of Theory 29
The Advantage of Learning a Good Design Methodology 31
Objectives of Good Design 32
Benefits of Good Design 33
Database-Design Methods 34
Traditional Design Methods 34
The Design Method Presented in This Book 36
Summary 40
Review Questions 41
Chapter 3: Terminology 43 Topics Covered in This Chapter 43
Why This Terminology Is Important 44
Value-Related Terms 45
Data 45
Information 45
Null 47
The Value of Nulls 48
The Problem with Nulls 50
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Structure-Related Terms 52
Table 52
Field 55
Record 56
View 57
Keys 59
Index 61
Relationship-Related Terms 62
Relationships 62
Types of Relationships 63
Types of Participation 68
Degree of Participation 69
Integrity-Related Terms 70
Field Specification 70
Data Integrity 71
Summary 72
Review Questions 73
PART II: THE DESIGN PROCESS 75
Chapter 4: Conceptual Overview 77 Topics Covered in This Chapter 77
The Importance of Completing the Design Process 78
Defining a Mission Statement and Mission Objectives 79
Analyzing the Current Database 80
Creating the Data Structures 82
Determining and Establishing Table Relationships 83
Determining and Defining Business Rules 84
Determining and Defining Views 85
Reviewing Data Integrity 85
Summary 86
Review Questions 88
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xvi Contents
Chapter 5: Starting the Process 91 Topics Covered in This Chapter 91
Conducting Interviews 91
Participant Guidelines 93
Interviewer Guidelines (These Are for You) 95
The Case Study: Mike’s Bikes 100
Defining the Mission Statement 101
The Well-Written Mission Statement 102
Composing a Mission Statement 104
Case Study 106
Defining the Mission Objectives 108
Well-Written Mission Objectives 108
Composing Mission Objectives 110
Case Study 114
Summary 115
Review Questions 116
Chapter 6: Analyzing the Current Database 119 Topics Covered in This Chapter 119
Getting to Know the Current Database 119
Paper-Based Databases 123
Legacy Databases 123
Conducting the Analysis 125
Looking at How Data Is Collected 125
Looking at How Information Is Presented 129
Conducting Interviews 133
Basic Interview Techniques 135
Before You Begin the Interview Process . . . 141
Interviewing Users 142
Reviewing Data Type and Usage 142
Reviewing the Samples 144
Reviewing Information Requirements 148
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Interviewing Management 157
Reviewing Current Information Requirements 158
Reviewing Additional Information Requirements 159
Reviewing Future Information Requirements 160
Reviewing Overall Information Requirements 161
Compiling a Complete List of Fields 162
The Preliminary Field List 162
The Calculated-Field List 170
Reviewing Both Lists with Users and Management 171
Case Study 172
Summary 177
Review Questions 179
Chapter 7: Establishing Table Structures 181 Topics Covered in This Chapter 181
Defining the Preliminary Table List 182
Identifying Implied Subjects 182
Using the List of Subjects 184
Using the Mission Objectives 189
Defining the Final Table List 191
Refining the Table Names 193
Indicating the Table Types 198
Composing the Table Descriptions 199
Associating Fields with Each Table 205
Refining the Fields 208
Improving the Field Names 208
Using an Ideal Field to Resolve Anomalies 213
Resolving Multipart Fields 216
Resolving Multivalued Fields 219
Refining the Table Structures 226
A Word About Redundant Data and Duplicate Fields 226
Using an Ideal Table to Refine Table Structures 227
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Establishing Subset Tables 235
Case Study 239
Summary 248
Review Questions 249
Chapter 8: Keys 251 Topics Covered in This Chapter 251
Why Keys Are Important 252
Establishing Keys for Each Table 252
Candidate Keys 253
Primary Keys 261
Alternate Keys 268
Non-keys 268
Table-Level Integrity 269
Reviewing the Initial Table Structures 270
Case Study 271
Summary 277
Review Questions 279
Chapter 9: Field Specifications 281 Topics Covered in This Chapter 281
Why Field Specifications Are Important 282
Field-Level Integrity 283
Anatomy of a Field Specification 284
General Elements 285
Physical Elements 293
Logical Elements 300
Using Unique, Generic, and Replica Field Specifications 308
Defining Field Specifications for Each Field in the Database 314
Case Study 316
Summary 318
Review Questions 320
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Chapter 10: Table Relationships 321 Topics Covered in This Chapter 321
Why Relationships Are Important 322
Types of Relationships 323
One-to-One Relationships 324
One-to-Many Relationships 327
Many-to-Many Relationships 330
Self-Referencing Relationships 337
Identifying Existing Relationships 341
Establishing Each Relationship 353
One-to-One and One-to-Many Relationships 353
The Many-to-Many Relationship 361
Self-Referencing Relationships 367
Reviewing the Structure of Each Table 373
Refining All Foreign Keys 374
Elements of a Foreign Key 374
Establishing Relationship Characteristics 381
Defining a Deletion Rule for Each Relationship 381
Identifying the Type of Participation for Each Table 387
Identifying the Degree of Participation for Each Table 390
Verifying Table Relationships with Users and Management 393
A Final Note 393
Relationship-Level Integrity 394
Case Study 395
Summary 400
Review Questions 402
Chapter 11: Business Rules 403 Topics Covered in This Chapter 403
What Are Business Rules? 404
Types of Business Rules 407
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Categories of Business Rules 409
Field Specific Business Rules 409
Relationship Specific Business Rules 410
Defining and Establishing Business Rules 412
Working with Users and Management 413
Defining and Establishing Field Specific Business Rules 413
Defining and Establishing Relationship Specific Business
Rules 421
Validation Tables 428
What Are Validation Tables? 430
Using Validation Tables to Support Business Rules 431
Reviewing the Business Rule Specifications Sheets 434
Case Study 437
Summary 442
Review Questions 445
Chapter 12: Views 447 Topics Covered in This Chapter 447
What Are Views? 447
Anatomy of a View 449
Data View 449
Aggregate View 454
Validation View 458
Determining and Defining Views 460
Working with Users and Management 461
Defining Views 462
Reviewing the Documentation for Each View 470
Case Study 472
Summary 477
Review Questions 478
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Chapter 13: Reviewing Data Integrity 481 Topics Covered in This Chapter 481
Why You Should Review Data Integrity 482
Reviewing and Refining Data Integrity 483
At the Table Level 483
At the Field Level 484
At the Relationship Level 484
At the Level of Business Rules 484
At the Level of Views 485
Assembling the Database Documentation 486
Done at Last! 487
Case Study—Wrap Up 487
Summary 488
PART III: OTHER DATABASE-DESIGN ISSUES 489
Chapter 14: Bad Design—What Not to Do 491 Topics Covered in This Chapter 491
Flat-File Design 492
Spreadsheet Design 493
Dealing with the Spreadsheet View Mind-set 495
Database Design Based on the Database Software 497
A Final Thought 498
Summary 499
Chapter 15: Bending or Breaking the Rules 501 Topics Covered in This Chapter 501
When May You Bend or Break the Rules? 501
Designing an Analytical Database 501
Improving Processing Performance 502
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xxii Contents
Documenting Your Actions 505
Summary 507
In Closing 509
PART IV APPENDIXES 511
Appendix A: Answers to Review Questions 513 Chapter 1 513
Chapter 2 514
Chapter 3 516
Chapter 4 517
Chapter 5 518
Chapter 6 520
Chapter 7 522
Chapter 8 525
Chapter 9 528
Chapter 10 530
Chapter 11 532
Chapter 12 533
Appendix B: Diagram of the Database-Design Process 537
Appendix C: Design Guidelines 555 Defining and Establishing Field Specific Business Rules 555
Defining and Establishing Relationship Specific Business
Rules 555
Elements of a Candidate Key 556
Elements of a Foreign Key 556
Elements of a Primary Key 557
Rules for Establishing a Primary Key 557
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Elements of the Ideal Field 557
Elements of the Ideal Table 558
Field-Level Integrity 558
Guidelines for Composing a Field Description 559
Guidelines for Composing a Table Description 559
Guidelines for Creating Field Names 560
Guidelines for Creating Table Names 560
Identifying Relationships 561
Identifying View Requirements 561
Interview Guidelines 562
Participant Guidelines 562
Interviewer Guidelines 562
Mission Statements 563
Mission Objectives 563
Relationship-Level Integrity 564
Resolving a Multivalued Field 564
Table-Level Integrity 565
Appendix D: Documentation Forms 567
Appendix E: Database-Design Diagram Symbols 571
Appendix F: Sample Designs 573
Appendix G: Recommended Reading 581
Glossary 583
References 599
Index 601
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xxv
Foreword
I don’t see Mike Hernandez as much as I used to. Both our professional
lives have changed a great deal since I first wrote the foreword to his
original edition. If nothing else, we travel less, and our paths cross less
often than they did. If you’ll indulge me, I might try to add that the en-
tire world has changed since that first edition. On the most mundane
level, my whole development life has changed, since I’ve bought into this
Microsoft .NET thing whole-heartedly and full-time. One thing that hasn’t
changed, however, is the constant need for data, and well-designed data.
Slapping together sophisticated applications with poorly designed data
will hurt you just as much now as when Mike wrote his first edition—
perhaps even more. Whether you’re just getting started developing with
data, or are a seasoned pro; whether you’ve read Mike’s previous book,
or this is your first time; whether you’re happier letting someone else
design your data, or you love doing it yourself—this is the book for you.
Mike’s ability to explain these concepts in a way that’s not only clear,
but fun, continues to amaze me.
—Ken Getz
October 10, 2002
From the First Edition . . . Perhaps you’re wondering why the world needs another book on data-
base design. When Mike Hernandez first discussed this book with me, I
wondered. But the fact is—as you may have discovered from leafing
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xxvi Foreword
through pages before landing here in the foreword—the world does need
a book like this one. You can certainly find many books detailing the
theories and concepts behind the science of database design, but you
won’t find many (if any) written from Mike’s particular perspective. He
has made it his goal to provide a book that is clearly based on the
sturdy principles of mathematical study, but has geared it toward prac-
tical use instead of theoretical possibilities. No matter what specific da-
tabase package you’re using, the concepts in this book will make sense
and will apply to your database-design projects.
I knew this was the book for me when I turned to the beginning of
Chapter 6 and saw this suggestion:
Do not adopt the current database structure as the basis for the
new database structure.
If I’d had someone tell me this when I was starting out on this database
developer path years ago I could have saved a ton of time! And that’s my
point here: Mike has spent many years designing databases for clients;
he has spent lots of time thinking, reading, and studying about the right
way to create database applications; and he has put it all here, on pa-
per, for the rest of us.
This book is full of the right stuff, illustrated with easy-to-understand
examples. That’s not to say that it doesn’t contain the hardcore infor-
mation you need to do databases right—it does, of course. But it’s
geared toward real developers, not theoreticians.
I’ve spent some time talking with Mike about database design. Over cof-
fee, in meetings, writing courseware, it’s always the same: Mike is pas-
sionate about this material. Just as the operating system designer
seeks the perfect, elegant algorithm, Mike spends his time looking for
just the right way to solve a design puzzle and—as you will read in this
book—how best to explain it to others. I’ve learned much of what I know
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Foreword xxvii
about database design from Mike over the years and feel sure that I
have a lot more to learn from this book. After reading through this con-
cise, detailed presentation of the information you need to know in order
to create professional databases, I’m sure you’ll feel the same way.
—Ken Getz
MCW Technologies
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Preface (Second Edition)
Life, as the most ancient of all metaphors insists, is a journey . . .
—JONATHAN RABAN FOR LOVE AND MONEY
I believe that learning about database design is an ongoing process. I’m always learning
more and more about the intricacies and nuances of design—and so will you.
—MICHAEL J. HERNANDEZ DATABASE DESIGN FOR MERE MORTALS
In the six years since the first edition of this book was published, I’ve
continued my journey along the database path. I’ve dug deeper into the
intracacies of design and probed further into the philosophy of good de-
sign. I’ve learned much from numerous conversations with my database
students and industry colleagues and from the correspondence I’ve had
with those who have read my book. As a result, I’ve been able to hone
my design methodology and revise some of its processes, making it
clearer and more thorough than ever before.
Although I’ll take a brief break (writing can be quite a mental exercise), I
know that my journey will soon continue. There is still so much more to
explore, discover, and learn. I find that designing and working with da-
tabases is much like mountain climbing—there’s always a new and ex-
citing challenge ahead of you! Perhaps six years from now, I’ll have a
chance to share my experiences with you once again.
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Acknowledgments
Despite what anyone tells you, writing is truly a cooperative effort. I am
so thankful that there are editors, colleagues, friends, and family who
continue to be ready and willing to lend their help. It is these people
who provide encouragement and keep you focused on the task at hand,
and it is to them that I extend my most heartfelt appreciation.
First, I wish to thank my editor, Mary O’Brien, for the opportunity to
write this new edition. Her patience, kindness, leadership, and steady
hand guided this project and helped me bring it to successful comple-
tion. I’d also like to thank Mary’s assistants, Alicia Carey, Stacie
Parillo, and Brenda Mulligan. Alicia and Stacey displayed great pa-
tience and provided unwavering support throughout the many months
I was working on this edition, and Brenda was an invaluable partner
throughout the production process. And a special thanks to John
Fuller and his production staff—great job, as always! A hearty thanks
to Tyrrell Albaugh for guiding the production process so smoothly, and
to Jennifer Kelland for her meticulous and thorough editing work. With
such a wonderful team as this, I just can’t imagine why I’d ever want to
write for anyone else.
Next, I’d like to acknowledge my distinguished technical review team:
Sandy Barker, Michael Blaha, Matt Greer, and Michelle Poolet. These
folks graciously and generously gave their time, effort, and expertise to
provide me with a wealth of valuable feedback and suggestions. This
book definitely benefitted from their contributions. Thanks once again
to all of you for your time and input and for helping to make this edition
even better than I first envisioned.
I want to extend a very special thanks to Ken Getz for once again provid-
ing the foreword for my book. Ken is a well-respected database/VB/
.NET expert, a colleague, and a good friend. I’m so pleased to have his
thoughts and comments at the beginning of the book.
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A special thanks also goes to all of those readers who took the time to
send me their thoughts and comments. I am humbled by their praise
and support and particularly appreciative of the good, constructive crit-
icism that eventually helped me to improve that material in this edition.
I also wish to thank all the academic institutions, government agencies,
and commercial organizations that have adopted my book and made it
“standard reading” for those just beginning their database careers. I am
honored by their support of my work.
Finally, I want to thank my wife, Kendra, for her unending patience
while I was enmeshed in my writing. Her help and support have been
invaluable, and yet again, I owe her a great debt. I would tell you exactly
how I feel about her, but she abhors any sort of PDA (public display of
affection). Instead of a big verbal hug, I’ll just say this:
Well, Ked, now we can take a nice, long, well-deserved break. . . .
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Preface (First Edition)
If the Lord Almighty had consulted me before embarking upon Creation, I should
have recommended something simpler. —ALFONSO X, KING OF CASTILE AND LEON
Creating a database can be like creating a universe, only more complicated. At least when the universe was
created, there was no one around to complain. —MICHAEL J. HERNANDEZ
It all started with a simple question: How do I properly design a
database?
It was a question that propelled me onto an interesting journey—a jour-
ney to find someone or some book that could provide the answer. This
journey has taken me to a number of bookstores and put me in the path
of many interesting and fascinating people. I’ve read a variety of books
on the subject, from the totally incomprehensible to the sorely lacking
in content, and had conversations with people ranging from those who
were in my position to those who really knew their craft. I was fortunate
to have a few people in the latter category become my mentors, and I
learned a great deal from them.
Books were a different story. There came a moment when I realized that
current books on database design were just not written for people like
me. If you had a background in mathematics, a computer science de-
gree, and had been working in the computer industry for some time,
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xxxiv Preface (First Edition)
then you were the audience the authors of these books were trying to
reach. Otherwise, there was very little available. The few attempts at
“simplified” texts simply failed to teach effectively, often because the au-
thors seemed to assume that the reader was simpleminded.
I believed that there should be a book for people who did not have high
levels of specialized education; a book that was straightforward and
easy to read, thorough but not tedious; a book that used examples that
were relatively easy to understand. So I wrote a special report on the
fundamentals of database design for a local publisher, and it met with
some success. Encouraged by this, I decided that someday I would write
a book on the complete process of relational database design.
Early in my journey, I became a successful database developer and in-
structor. I’ve developed databases for a number of diverse organizations
and businesses and have taken pleasure in instructing people on how
to use a variety of database software programs. Throughout all this I’ve
kept my sights on my goal.
It was at the 1995 Database Summit in Seattle, Washington, that I met
Kathleen Tibbetts, a Developers Press editor for Addison-Wesley. At that
moment my journey took quite a positive turn. She was looking for peo-
ple with something to say, and I was definitely that type of person.
Kathleen listened very patiently to the story of the journey upon which I
had embarked. She determined that this would be a good time for me to
work on realizing my goal—to finally commit to paper all that I had
learned about database design.
The book you now hold in your hands is a result of the culmination of
this particular journey. I’ve shaped and molded the knowledge I accu-
mulated into what I believe is a clear and straightforward database-
design method. I’ve tried very hard to make it accessible to everyone,
regardless of previous experience. I have sought a presentation that
would be easier to learn and understand than traditional design meth-
ods, yet would yield the same results.
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I believe that learning about database design is an ongoing process. I’m
always learning more and more about the intricacies and nuances of
design—and so will you. Database design is more of an art than an ex-
act science, involving as much intuition as pure theoretical and techni-
cal knowledge. It also involves communication skills and the ability to
see things in the long term, as well as the short term. Database design
can be a fascinating subject once you really get into it.
Acknowledgments
I’ve discovered that writing a book is something of a cooperative effort. I
am thankful that there are always editors, colleagues, friends, and fam-
ily who are ready and willing to lend their help. It is these people who
provide encouragement and keep you focused on the task at hand.
Without them, you could easily “put it off until tomorrow.”
First and foremost, I would like to thank Kathleen Tibbetts at Addison-
Wesley for her unwavering support and for providing me with the oppor-
tunity to write this book. She has been just as enthusiastic about this
project as I have been. I look forward to working with her on further
projects.
Next, my deepest thanks to my good friend, colleague, and technical ed-
itor, Jim Booth. I have a great deal of respect for Jim’s knowledge on the
subject of database design, and his comments have been invaluable. He
and I have a thick porterhouse steak and a bottle of fine red wine wait-
ing for us once this book is out on the market.
I also owe a debt of gratitude to my good friend and colleague Christo-
pher R. Weber. In spite of a busy consulting and lecture schedule, Chris
reviewed a number of chapters and provided valuable feedback. Now, if
we could both find the time to sit down and discuss music . . . (we’re
both musicians.)
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xxxvi Preface (First Edition)
I’d like to acknowledge some of the many people who have shared their
experience and knowledge with me and have had a positive influence on
my career in the field of database management: Karen Watterson, Mike
Johnson, Karl Fischer, Paul Litwin, John Viescas, Ken Getz, and Gre-
gory Piercy. My thanks to you all.
My sincerest and deepest appreciation goes to my very dear friend and
mentor, Alastair Black. Not only was he gracious enough to review every
word in the entire book; he and his wife, Julia, opened their home to me
and treated me as one of their own. His immeasurable and invaluable
help in the writing of this book cannot be overstated. I’ve learned more
about the craft of writing in these past months than at any other time in
my professional or personal life.
Last, but certainly not least, a special thanks to my wife, Kendra. Every
married author realizes, by the end of the work, how much he owes to the
patience of the spouse and is moved to recognize the priceless contribu-
tion of interest and forbearance. But I am enjoined not to make as much
of this as it deserves, because Kendra strongly opposes public displays of
affection (PDAs as she calls them), whether in person or in print. So the
only thing I’ll say is this: Thanks, Ked. Now we can resume a normal life.
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Introduction
Plain cooking cannot be entrusted to plain cooks. —COUNTESS MORPHY
In the past, the process of designing a database has been a task per-
formed by information technology (IT) personnel and professional data-
base developers. These people usually had mathematical, computer
science, or systems design backgrounds and typically worked with large
mainframe databases. Many of them were experienced programmers
and had coded a number of database application programs consisting of
thousands of lines of code. (And these people were usually very over-
worked due to the nature and importance of their work!)
People designing database systems at that time needed to have a solid
educational background because most of the systems they created were
meant to be used companywide. Even when creating databases for sin-
gle departments within a company or for small businesses, database de-
signers still required extensive formal training because of the
complexity of the programming languages and database application
programs that they were using. As technology advanced, however, those
educational requirements evolved.
Since the mid-1980s, many software vendors have developed database
software programs that run on desktop computers and can be more
easily programmed to collect, store, and manage data than their main-
frame counterparts. They have also produced software that allows
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groups of people to access and share centralized data within a variety of
environments, such as client/server architectures on computers con-
nected within local-area networks (LANs) and wide-area networks
(WANs), and even via the Internet. People within a company or organiza-
tion are no longer strictly dependent on mainframe databases or on
having their information needs met by centralized IT departments. Over
the years, vendors have added new features and enhanced the tool sets
in their database software, enabling database developers to create more
powerful and flexible database applications. They’ve also improved the
ease with which the software can be used, inspiring many people to cre-
ate their own database applications. Today’s database software greatly
simplifies the process of creating efficient database structures and intu-
itive user interfaces.
Most programs provide sample database structures that you can copy
and alter to suit your specific needs. Although you might initially think
that it would be quite advantageous for you to use these sample struc-
tures as the basis for a new database, you should stop and reconsider
that move for a moment. Why? Because you could easily and unwit-
tingly create an improper, inefficient, and incomplete design. Then you
would eventually encounter problems in what you believed to be a de-
pendable database design. This, of course, raises the question, “What
types of problems would I encounter?”
Most problems that surface in a database fall into two categories: appli-
cation problems and data problems. Application problems include such
things as problematic data entry/edit forms, confusing menus, confus-
ing dialog boxes, and tedious task sequences. These problems typically
arise when the database developer is inexperienced, is unfamiliar with a
good application-design methodology, or knows too little about the soft-
ware he’s using to implement the database. Problems of this nature are
common and important to address, but they are beyond the scope of
this work.
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Introduction xxxix
Data problems, on the other hand, include such things as missing data,
incorrect data, mismatched data, and inaccurate information. Poor data-
base design is typically the root cause of these types of problems. A data-
base will not fulfill an organization’s information requirements if it is not
structured properly. Although poor design is typically generated by a da-
tabase developer who lacks knowledge of good database-design princi-
ples, it shouldn’t necessarily reflect negatively on the developer. Many
people, including experienced programmers and database developers,
have had little or no instruction in any form of database-design method-
ology. Many are unaware that design methodologies even exist. Data
problems and poor design are the issues that this work will address.
What’s New in the Second Edition
I revised this edition to improve readability, update or extend existing
topics, add new content, and enhance its educational value. Here is a
list of the changes you’ll find in this edition:
• Much of the text has been rewritten to improve clarity and reader
comprehension.
• Many of the figures and illustrations have been revised to improve
clarity.
❖ Note One good way to solve many of your application prob- lems is to purchase and study third-party “developer” books that
cover the software you’re using. Such books discuss application-
design issues, advanced programming techniques, and various
tips and tricks that you can use to improve and enhance an ap-
plication. Armed with these new skills, you can revamp and fine-
tune the database application so that it works correctly,
smoothly, and efficiently.
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xl Introduction
• New figures and illustrations have been added as warranted by
revisions of or additons to existing text.
• Discussions of relational database management systems and the
relational model in Chapter 1 have both been expanded to include
brief content on recent technological advances and general indus-
try direction.
• The premise behind the design methodology presented in this
book is explained in Chapter 2.
• Discussion of nulls and the many-to-many relationship in
Chapter 3 have both been expanded to provide greater detail
on these subjects.
• Web-page-based examples are now included as appropriate in
Chapter 6.
• Discussions of multivalued fields and the subset tables in
Chapter 7 have both been expanded to provide greater detail
on these subjects.
• The discussion of primary keys in Chapter 8 has been expanded
to provide greater detail on this subject.
• The Field Specifications sheet has been updated and redesigned
for improved flow and readability.
• The discussion of the Data Type field specification element in
Chapter 9 has been expanded to include an introduction to Struc-
tured Query Language (SQL) data types.
• Discussions of self-referencing relationships and the Deny, Nullify,
and Set Default deletion rules have been added to Chapter 10.
• Review questions have been added at the end of Chapters 1 through
12, and the answers to the questions appear in Appendix A.
• A flowchart of the design process has been provided as a quick
reference tool and is included in Appendix B.
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Introduction xli
• All of the various design guidelines have been compiled in
Appendix C.
• A glossary has been added to provide a quick reference for various
terms used throughout the book.
• The accompanying CD includes files in Adobe Acrobat PDF for-
mat. These files contain the material in Appendixes B through F.
Who Should Read This Book
No previous background in database design is necessary to read this
book. The reason you have this book in your hands is to learn how to
design a database properly. If you’re just getting into database manage-
ment and you’re thinking about developing your own databases, this
book will be very valuable to you. It’s better that you learn how to create
a database properly from the beginning than that you learn by trial and
error. The latter method takes much longer, believe me.
If you fall into the category of those people who have been working with
database programs for a while and are ready to begin developing new
databases for your company or business, you should read this book.
You probably have a good feel for what a good database structure
should look like, but aren’t quite sure how database developers arrive at
an effective design. Maybe you’re a programmer who has created a
number of databases following a few basic guidelines, but you have al-
ways ended up writing a lot of code to get the database to work properly.
If this is the case, this book is also for you.
It would be a good idea for you to read this book even if you already have
some background in database design. Perhaps you learned a design
methodology back in college or attended a database class that discussed
design, but your memory is vague about some details, or there were
parts of the design process that you just did not completely understand.
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xlii Introduction
Those points with which you had difficulty will finally become clear once
you learn and understand the design process presented in this book.
This book is also appropriate for those of you who are experienced data-
base developers and programmers. Although you may already know
many of the aspects of the design process that are presented here, you’ll
probably find that there are some elements that you’ve never before en-
countered or considered. You may even come up with fresh ideas about
how to design your databases by reviewing the material in this book be-
cause many of the design processes familiar to you are presented here
from a different viewpoint. At the very least, this book can serve as a
great refresher course in database design.
The Purpose of This Book
In general terms, there are three phases to the overall database-devel-
opment process.
1. Logical design: The first phase involves determining and defining
tables and their fields, establishing primary and foreign keys,
establishing table relationships, and determining and establishing
the various levels of data integrity.
❖ Note Those of you who have a burning desire to immerse yourselves in the depths of the database field (i.e., to learn the in-
tricacies of database theory and design, analysis, implementa-
tion, administration, application development, and so on) should
make a point of reading most of the books on my recommended
reading list. Although I do not cover any of the aforementioned
topics, my book does serve as the beginning of your journey into
the realm of the database professional.
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Introduction xliii
2. Physical implementation: The second phase entails creating the ta-
bles, establishing key fields and table relationships, and using the
proper tools to implement the various levels of data integrity.
3. Application development: The third phase involves creating an ap-
plication that allows a single user or group of users to interact with
the data stored in the database. The application-development
phase itself can be divided into separate processes, such as deter-
mining end-user tasks and their appropriate sequences, determin-
ing information requirements for report output, and creating a
menu system for navigating the application.
You should always go through the logical design first and execute it as
completely as possible. After you’ve created a sound structure, you can
then implement it within any database software you choose. As you be-
gin the implementation phase, you may find that you need to modify the
database structure based on the pros and cons or strengths and weak-
nesses of the database software you’ve chosen. You may even decide to
make structural modifications to enhance data-processing performance.
Performing the logical design first ensures that you make conscious, me-
thodical, clear, and informed decisions concerning the structure of your
database. As a result, you help minimize the potential number of further
structural modifications you might need to make during the physical-
implementation and application-development phases.
This book deals with only the logical-design phase of the overall devel-
opment process, and the book’s main purpose is to explain the process
of relational database design without using the advanced, orthodox
methodologies found in an overwhelming majority of database-design
books. I’ve taken care to avoid the complexities of these methodologies
by presenting a relatively straightforward, commonsense approach to
the design process. I also use a simple and straightforward data-model-
ing method as a supplement to this approach, and present the entire
process as clearly as possible and with a minimum of technical jargon.
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xliv Introduction
There are many database-design books out on the market that include
chapters on implementing the database within a specific database prod-
uct, and some books even seem to meld the design and implementation
phases together. (I’ve never particularly agreed with the idea of combin-
ing these phases, and I’ve always maintained that a database developer
should perform the logical-design and implementation phases sepa-
rately to ensure maximum focus, effectiveness, and efficiency.) The
main drawback that I’ve encountered with these types of books is that it
can be difficult for a reader to obtain any useful or relevant information
from the implementation chapters if he or she doesn’t work with the
particular database software or programming language that the book
incorporates. It is for this reason that I decided to write a book that fo-
cuses strictly on the logical design of the database.
This book should be easier to read than other books you may have en-
countered on the subject. Many of the database-design books on the
market are highly technical and can be difficult to assimilate. I think
most of these books can be confusing and overwhelming if you are not a
computer science major, database theorist, or experienced database de-
veloper. The design principles you’ll learn within these pages are easy to
understand and remember, and the examples are common and generic
enough to be relevant to a wide variety of situations.
Most people I’ve met in my travels around the country have told me that
they just want to learn how to create a sound database structure with-
out having to learn about normal forms or advanced mathematical the-
❖ Note I do not cover implementation issues, SQL, or applica- tion-programming issues in this work, but there are various
books that I do recommend on these topics. You can review
my recommendations by accessing my Web site at http:// www.ForMereMortals.com.
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Introduction xlv
ories. Many people are not as worried about implementing a structure
within a specific database software as they are about learning how to
optimize their data structures and how to impose data integrity. In this
book, you’ll learn how to create efficient database structures, how to
impose several levels of data integrity, as well as how to relate tables to-
gether to obtain information in an almost infinite number of ways. Don’t
worry; this isn’t as difficult a task as you might think. You’ll be able to
accomplish all of this by understanding a few key terms and by learning
and using a specific set of commonsense techniques and concepts.
You’ll also learn how to analyze and leverage an existing database, de-
termine information requirements, and determine and implement busi-
ness rules. These are important topics because many of you will
probably inherit old databases that you’ll need to revamp using what
you’ll learn by reading this book. They’ll also be just as important when
you create a new database from scratch.
When you finish reading this book, you’ll have the knowledge and tools
necessary to create a good relational database structure. I’m confident
that this entire approach will work for a majority of developers and the
databases they need to create.
How to Read This Book
I strongly recommend that you read this book in sequence from begin-
ning to end, regardless of whether you are a novice or a professional.
You’ll keep everything in context this way and avoid the confusion that
generally comes from being unable to see the “big picture” first. It’s also
a good idea to learn the process as a whole before you begin to focus on
any one part.
If you are reading this book to refresh your design skills, you could read
just those sections that are of interest to you. As much as possible, I’ve
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xlvi Introduction
tried to write each chapter so that it could stand on its own; nonethe-
less, I would still recommend that you glance through each of the chap-
ters to make sure that you’re not missing any new ideas or points on
design that you may not have considered up to now.
How This Book Is Organized
Here’s a brief overview of what you’ll find in each part and each chapter.
Part I: Relational Database Design
This section provides an introduction to databases, the idea of data-
base design, and some of the terminology you’ll need to be familiar
with in order to learn and understand the design process presented in
this book.
Chapter 1, The Relational Database, provides a brief discussion of the types of databases you’ll encounter, common database models, and a
brief history of the relational database.
Chapter 2, Design Objectives, explores why you should be concerned with design, points out the objectives and advantages of good design,
and provides a brief introduction to normalization and normal forms.
Chapter 3, Terminology, covers the terms you need to know in order to learn and understand the design methodology presented in this book.
Part II: The Design Process
Each aspect of the database-design process is discussed in detail in
Part II, including establishing table structures, assigning primary keys,
setting field specifications, establishing table relationships, setting up
views, and establishing various levels of data integrity.
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Chapter 4, Conceptual Overview, provides an overview of the design process, showing you how the different components of the process fit
together.
Chapter 5, Starting the Process, covers how to define a mission state- ment and mission objectives for the database, both of which provide you
with an initial focus for creating your database.
Chapter 6, Analyzing the Current Database, covers issues concerning the existing database. We look at reasons for analyzing the current da-
tabase, how to look at current methods of collecting and presenting
data, why and how to conduct interviews with users and management,
and how to compile initial field lists.
Chapter 7, Establishing Table Structures, covers topics such as deter- mining and defining what subjects the database should track, associat-
ing fields with tables, and refining table structures.
Chapter 8, Keys, covers the concept of keys and their importance to the design process, as well as how to define candidate and primary keys for
each table.
Chapter 9, Field Specifications, covers a topic that a number of data- base developers tend to minimize. Besides indicating how each field is
created, field specifications determine the very nature of the values a
field contains. Topics in this chapter include the importance of field
specifications, types of specification characteristics, and how to define
specifications for each field in the database.
Chapter 10, Table Relationships, explains the importance of table rela- tionships, types of relationships, setting up relationships, and estab-
lishing relationship characteristics.
Chapter 11, Business Rules, covers types of business rules, determining and establishing business rules, and using validation tables. Business
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xlviii Introduction
rules are very important in any database because they provide a distinct
level of data integrity.
Chapter 12, Views, looks into the concept of views and why they are important, types of views, and how to determine and set up views.
Chapter 13, Reviewing Data Integrity, reviews each of the levels of in- tegrity that have been defined and discussed in previous chapters. Here
you learn that it’s a good idea to review the final design of the database
structure to ensure that you’ve imposed data integrity as completely as
you can.
Part III: Other Database-Design Issues
This section deals with topics such as avoiding bad design and bending
the rules set forth in the design process.
Chapter 14, Bad Design—What Not to Do, covers the types of designs you should avoid, such as a flat-file design and a spreadsheet design.
Chapter 15, Bending or Breaking the Rules, discusses those rare in- stances in which it may be necessary to stray from the techniques and
concepts of the design process. This chapter tells you when you should
consider bending the rules, as well as how it should be done.
Part IV: Appendixes
Appendix A, Answers to Review Questions, contains the answers to all of the review questions in Chapters 1 through 12.
Appendix B, Diagram of the Database Design Process, provides a dia- gram that maps the entire database design process.
Appendix C, Design Guidelines, provides an easy reference to the vari- ous sets of design guidelines that appear throughout the book.
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Introduction xlix
Appendix D, Documentation Forms, provides blank copies of the Field Specifications, Business Rule Specifications, and View Specifications
sheets, which you can copy and use on your database projects.
Appendix E, Database Design Diagram Symbols, contains a quick and easy reference to the diagram symbols used throughout the book.
Appendix F, Sample Designs, contains sample database designs that can serve as the basis for ideas for databases you may want or need to
create.
Appendix G, Recommended Reading, provides a list of books that you should read if you are interested in pursuing an in-depth study of data-
base technology.
Glossary contains concise definitions of various words and phrases used throughout the book.
A Word About the Examples and Techniques in This Book
You’ll notice that there are a wide variety of examples in this book. I’ve
made sure that they are as generic and relevant as possible. However,
you may notice that several of the examples are rather simplified, in-
complete, or even on occasion incorrect. Believe it or not, I created them
that way on purpose.
I’ve created some examples with errors so that I could illustrate specific
concepts and techniques. Without these examples, you wouldn’t see how
the concepts or techniques are put to use, as well as the results you
should expect from using them. Other examples are simple because,
IMPORTANT: READ THIS SECTION!
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l Introduction
once again, the focus is on the technique or concept and not on the ex-
ample itself. For instance, there are many ways that you can design an
order-tracking database. However, the structure of the sample order-
tracking database I use in this book is simple because the focus is spe-
cifically on the design process, not on creating an elaborate order-
tracking database system.
So what I’m really trying to emphasize here is this:
Focus on the concept or technique and its intended results, not
on the example used to illustrate it.
A New Approach to Learning
Here’s an approach to learning the design process (or pretty much any-
thing else, for that matter) that I’ve found very useful in my database-
design classes.
Think of all the techniques used in the design process as a set of tools;
each tool (or technique) is used for a specific purpose. The idea here is
that once you learn generically how a tool is used, you can then use
that tool in any number of situations. The reason you can do this is be-
cause you use the tool the same way in each situation.
Take a Crescent wrench, for example. Generically speaking, you use a
Crescent wrench to fasten and unfasten a nut to a bolt. You open or
close the jaw of the wrench to fit a given bolt by using the adjusting
screw located on the head of the wrench. Now that you have that clear,
try it out on a few bolts. Try it on the legs of an outdoor chair, or the
valve cover on an engine, or the side panel of an outdoor cooling unit, or
the hinge plates of an iron gate. Do you notice that regardless of where
you encounter a nut and bolt, you can always fasten and unfasten the
nut by using the Crescent wrench in the same manner?
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Introduction li
The tools used to design a database work in exactly the same way.
Once you understand how a tool is used generically, it will work the
same way regardless of the circumstances under which it is used. For
instance, consider the tool (or technique) for decomposing a field value.
Say you have a single ADDRESS field in a CUSTOMERS table that con-
tains the street address, city, state, and zip code for a given customer.
You’ll find it difficult to use this field in your database because it con-
tains more than one item of data; you’ll certainly have a hard time re-
trieving information for a particular city or sorting the information by a
specific zip code.
The solution to this apparent dilemma is to decompose the ADDRESS field
into smaller fields. You do this by identifying the distinct items that
make up the value of the field, and then treating each item as its own
separate field. That’s all there is to it! This process constitutes a “tool”
that you can now use on any field containing a value composed of two
or more distinct data items, such as these sample fields. Figure I.1
shows the results of the decomposition process.
❖ Note You’ll learn more about decomposing field values in Chapter 7, “Establishing Table Structures.”
Figure I.1. Decomposing fields containing multiple data items.
Current Field Name Sample Value New Field Names
Address 7402 Kingman Dr., Seattle, WA 98012 Street Address, City, State, Zip Code
Phone (206) 555-5555 Area Code, Phone Number
Name Michael J. Hernandez First Name, Middle Initial, Last Name
EmployeeCode ITDEV0516 Department, Category, ID Number
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lii Introduction
You can use all of the techniques (“tools”) that are part of the design
process presented in this book in the same manner. You’ll be able to de-
sign a sound database structure using these techniques regardless of
the type of database you need to create. Just be sure to remember this:
Focus on the concept or technique being presented and its
intended results, not on the example used to illustrate it.
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Part I Relational Database Design
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From the Library of Stephen Benoit
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3
1 The Relational Database
A fish must swim three times— in water, in butter, and in wine.
—POLISH PROVERB
Topics Covered in This Chapter
Types of Databases
Early Database Models
The Relational Database Model
Relational Database Management System
Beyond the Relational Model
What the Future Holds
Summary
Review Questions
The relational database has been in existence for over 25 years. It has
spawned a multi-billion dollar industry, is the most widely used type
of database in the world today, and is an essential part of our every-
day lives. It is very likely that you are using a relational database ev-
ery time you purchase goods at a store, make travel plans with your
travel agent, check out a book at the library, or make a purchase on
the Internet.
Before we delve into the design process, let’s take a look at a brief his-
tory of the relational database—where it has come from, where it is
now, and where it’s going in the future.
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4 Chapter 1 The Relational Database
Types of Databases
What is a database? As you probably know, a database is an organized
collection of data used for the purpose of modeling some type of organi-
zation or organizational process. It really doesn’t matter whether you’re
using paper or a computer software program to collect and store the
data. As long as you’re gathering data in some organized manner for a
specific purpose, you’ve got a database. Throughout the remainder of
this discussion, we’ll assume that you’re using a computer software
program to collect and maintain your data.
There are two types of databases found in database management, oper-
ational databases and analytical databases.
Operational databases are the backbone of many companies, organiza-
tions, and institutions throughout the world today. This type of
database is primarily used in on-line transaction processing (OLTP) sce-
narios, that is, in situations where there is a need to collect, modify,
and maintain data on a daily basis. The type of data stored in an oper-
ational database is dynamic, meaning that it changes constantly and
always reflects up-to-the-minute information. Organizations, such as
retail stores, manufacturing companies, hospitals and clinics, and pub-
lishing houses, use operational databases because their data is in a
constant state of flux.
In contrast, analytical databases are primarily used in on-line analyti-
cal processing (OLAP) scenarios, where there is a need to store and
track historical and time-dependent data. An analytical database is a
valuable asset when there is a need to track trends, view statistical
data over a long period of time, and make tactical or strategic business
projections. This type of database stores static data, meaning that the
data is never (or very rarely) modified. The information gleaned from an
analytical database reflects a point-in-time snapshot of the data.
Chemical labs, geological companies, and marketing-analysis firms are
examples of organizations that use analytical databases.
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Early Database Models 5
Analytical databases often use data from operational databases as their
main data source, so there can be some amount of association between
them; nevertheless, operational and analytical databases fulfill very
specific types of data-processing needs, and creating their structures
requires radically different design methodologies. This book focuses on
designing an operational database because it is still the most widely
used type of database in the world today.
Early Database Models
In the days before the relational database model, two data models were
commonly used to maintain and manipulate data—the hierarchical
database model and the network database model.
Some of the terms you’ll encounter in this section are explained in
more detail in Chapter 3, “Terminology.”
The Hierarchical Database Model
Data in this type of database is structured hierarchically and is typi-
cally diagrammed as an inverted tree. A single table in the database
acts as the “root” of the inverted tree and other tables act as the
❖ Note Although use of these models is rapidly waning, I’ve pro- vided a brief overview of each for historical purposes. In an
overall sense, I believe it is useful for you to know what preceded
the relational model so that you have a basic understanding of
what led to its creation and evolution.
In the following overview I briefly describe how the data in each
model is structured and accessed, how the relationship between
a pair of tables is represented, and one or two of the advantages
or disadvantages of each model.
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6 Chapter 1 The Relational Database
branches flowing from the root. Figure 1.1 shows a diagram of a typi-
cal hierarchical database structure.
A relationship in a hierarchical database is represented by the term
parent/child. In this type of relationship, a parent table can be associ-
ated with one or more child tables, but a single child table can be associ-
ated with only one parent table. These tables are explicitly linked via a
pointer or by the physical arrangement of the records within the tables. A
user accesses data within this model by starting at the root table and
working down through the tree to the target data. This access method
requires the user to be very familiar with the structure of the database.
Agents Database In the example shown in Figure 1.1, an agent books several entertainers, and each entertainer has his own
schedule. An agent also maintains a number of clients whose
entertainment needs are met by the agent. A client books engage-
ments through the agent and makes payments to the agent for
his services.
Payments
Clients
Agents
Entertainers
Schedule Engagements
Figure 1.1. Diagram of a typical hierarchical database.
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Early Database Models 7
One advantage to using a hierarchical database is that a user can
retrieve data very quickly because there are explicit links between the
table structures. Another advantage is that referential integrity is built
in and automatically enforced. This ensures that a record in a child
table must be linked to an existing record in a parent table, and that a
record deleted in the parent table will cause all associated records in
the child table to be deleted as well.
A problem occurs in a hierarchical database when a user needs to store
a record in a child table that is currently unrelated to any record in a
parent table. Consider an example using the Agents database shown in
Figure 1.1. A user cannot enter a new entertainer in the ENTERTAIN-
ERS table until the entertainer is assigned to an agent in the AGENTS
table. Recall that a record in a child table (in this case, ENTERTAIN-
ERS) must be related to a record in the parent table (AGENTS). Yet in
real life, entertainers commonly sign up with the agency well before
they are assigned to specific agents. This scenario is difficult to model
in a hierarchical database. The rules can be bent without breaking
them if a dummy agent record is inserted in the AGENTS table; how-
ever, this option is not really optimal.
This type of database cannot support complex relationships, and there
is often a problem with redundant data. For example, there is a many-
to-many relationship between clients and entertainers; an entertainer
will perform for many clients, and a client will hire many entertainers.
You can’t directly model this type of relationship in a hierarchical data-
base, so you’ll have to introduce redundant data into both the
SCHEDULE and ENGAGEMENTS tables.
• The SCHEDULE table will now have client data (such as client
name, address, and phone number) to show for whom and where
each entertainer is performing. This particular data is redun-
dant because it is currently stored in the CLIENTS table.
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8 Chapter 1 The Relational Database
• The ENGAGEMENTS table will now contain data on entertainers
(such as entertainer name, phone number, and type of enter-
tainer) to indicate which entertainers are performing for a given
client. This data is redundant as well because it is currently
stored in the ENTERTAINERS table.
The problem with this redundancy is that it opens up the possibility of
allowing a user to enter a single piece of data inconsistently. This, in
turn, can result in producing inaccurate information.
A user can solve this problem in a roundabout manner by creating one
hierarchical database specifically for entertainers and another specifi-
cally for agents. The new Entertainers database will contain only the
ENTERTAINERS table, and the revised Agents database will contain
the AGENTS, CLIENTS, PAYMENTS, and ENGAGEMENTS tables. The
SCHEDULE table is no longer needed in the Entertainers database
because you can define a logical child relationship between the
ENGAGEMENTS table in the Agents database and the ENTERTAIN-
ERS table in the Entertainers database. With this relationship in place,
you can retrieve a variety of information, such as a list of booked enter-
tainers for a given client or a performance schedule for a given
entertainer. Figure 1.2 shows a diagram of the new model.
As you see, a person designing a hierarchical database must be able to
recognize the need to use this technique for a many-to-many relation-
ship. Here the need is relatively obvious, but many relationships are
more obscure and may not be discovered until very late in the design
process or, more disturbingly, well after the database has been put into
operation.
The hierarchical database lent itself well to the tape storage systems
used by mainframes in the 1970s and was very popular in companies
that used those systems. But, despite the fact that the hierarchical
database provided fast and direct access to data and was useful in a
number of circumstances, it was clear that a new database model was
From the Library of Stephen Benoit
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Early Database Models 9
needed to address the growing problems of data redundancy and com-
plex relationships among data.
The Network Database Model
The network database was, for the most part, developed as an
attempt to address some of the problems of the hierarchical data-
base. The structure of a network database is represented in terms of
nodes and set structures. Figure 1.3 shows a diagram of a typical net-
work database.
Agents Database In the example shown in Figure 1.3, an agent represents a number of clients and manages a number of enter-
tainers. Each client schedules any number of engagements and
makes payments to the agent for his or her services. Each enter-
tainer performs a number of engagements and may play a variety
of musical styles.
Agents
ClientsEntertainers
Engagements Payments
Entertainers Database
Agents Database
Logical Child Relationship
Figure 1.2. Using two hierarchical databases to resolve a many-to-many relationship.
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10 Chapter 1 The Relational Database
A node represents a collection of records, and a set structure estab-
lishes and represents a relationship in a network database. It is a
transparent construction that relates a pair of nodes together by using
one node as an owner and the other node as a member. (This is a valu-
able improvement on the parent/child relationship.) A set structure
supports a one-to-many relationship, which means that a record in the
owner node can be related to one or more records in the member node,
but a single record in the member node is related to only one record in
the owner node. Additionally, a record in the member node cannot exist
without being related to an existing record in the owner node. For
example, a client must be assigned to an agent, but an agent with no
clients can still be listed in the database. Figure 1.4 shows a diagram
of a basic set structure.
One or more sets (connections) can be defined between a specific pair
of nodes, and a single node can also be involved in other sets with
other nodes in the database. In Figure 1.3, for instance, the CLIENTS
node is related to the PAYMENTS node via the Make set structure. It is
Agents
Clients
Engagements
Entertainers
Musical StylesPayments
Represent Manage
Make Schedule PlayPerform
Figure 1.3. Diagram of a typical network database.
From the Library of Stephen Benoit
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Early Database Models 11
also related to the ENGAGEMENTS node via the Schedule set struc-
ture. Along with being related to the CLIENTS node, the ENGAGE-
MENTS node is related to the ENTERTAINERS node via the Perform set
structure.
A user can access data within a network database by working through
the appropriate set structures. Unlike the hierarchical database, where
access must begin from a root table, a user can access data from within
the network database, starting from any node and working backward
or forward through related sets. Consider the Agents database in
Figure 1.3 once again. Say a user wants to find the agent who booked
a specific engagement. She begins by locating the appropriate engage-
ment record in the ENGAGEMENTS node, and then determines which
client “owns” that engagement record via the Schedule set structure. Fi-
nally, she identifies the agent that “owns” the client record via the Rep-
resent set structure. The user can answer a wide variety of questions as
long as she navigates properly through the appropriate set structures.
One advantage the network database provides is fast data access. It
also allows users to create queries that are more complex than those
Agents
Clients
Represent
Owner Node
Set Structure
Member Node
1
M
Figure 1.4. A basic set structure.
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12 Chapter 1 The Relational Database
they created using a hierarchical database. A network database’s main
disadvantage is that a user has to be very familiar with the structure of
the database in order to work through the set structures. Consider the
Agents database in Figure 1.3 once again. It is incumbent on the user
to be familiar with the appropriate set structures if she is to determine
whether a particular engagement has been paid. Another disadvantage
is that it is not easy to change the database structure without affecting
the application programs that interact with it. Recall that a relation-
ship is explicitly defined as a set structure in a network database. You
cannot change a set structure without affecting the application pro-
grams that use this structure to navigate through the data. If you
change a set structure, you must also modify all references made from
within the application program to that structure.
Although the network database was clearly a step up from the hierar-
chical database, a few people in the database community believed that
there must be a better way to manage and maintain large amounts of
data. As each data model emerged, users found that they could ask
more complex questions, thereby increasing the demands made upon
the database. And so, we come to the relational database model.
The Relational Database Model
The relational database was first conceived in 1969 and has arguably
become the most widely used database model in database manage-
ment today. The father of the relational model, Dr. Edgar F. Codd, was
an IBM research scientist in the late 1960s and was at that time look-
ing into new ways to handle large amounts of data. His dissatisfaction
with the database models and database products of the time led him to
begin thinking of ways to apply the disciplines and structures of math-
ematics to solve the myriad of problems he had been encountering.
Being a mathematician by profession, he strongly believed that he
could apply specific branches of mathematics to solve problems, such
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The Relational Database Model 13
as data redundancy, weak data integrity, and a database structure’s
overdependence on its physical implementation.
Dr. Codd formally presented his new relational model in a landmark
work entitled “A Relational Model of Data for Large Shared Data-
banks”1 in June of 1970. He based his new model on two branches of
mathematics—set theory and first-order predicate logic. Indeed, the
name of the model itself is derived from the term relation, which is part
of set theory. (A widely held misconception is that the relational model
derives its name from the fact that tables within a relational database
can be related to one another.)
A relational database stores data in relations, which the user perceives
as tables. Each relation is composed of tuples, or records, and attributes,
or fields. (I’ll use the terms tables, records, and fields throughout the
remainder of the book.) The physical order of the records or fields in a
table is completely immaterial, and each record in the table is identified
by a field that contains a unique value. These are the two characteris-
tics of a relational database that allow the data to exist independently of
the way it is physically stored in the computer. As such, a user isn’t
required to know the physical location of a record in order to retrieve its
data. This is unlike the hierarchical and network database models, in
which knowing the layout of the structures is crucial to retrieving data.
The relational model categorizes relationships as one-to-one, one-to-
many, and many-to-many. (These relationships are covered in detail in
Chapter 10.) A relationship between a pair of tables is established
implicitly through matching values of a shared field. In Figure 1.5, for
example, the CLIENTS and AGENTS tables are related via an AGENT ID
field; a specific client is associated with an agent through a matching
AGENT ID. Likewise, the ENTERTAINERS and ENGAGEMENTS tables
are related via an ENTERTAINER ID; a record in the ENTERTAINERS table
1. Edgar F. Codd, “A Relational Model of Data for Large Shared Databanks,” Communica- tions of the ACM, June 1970, 377–87.
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14 Chapter 1 The Relational Database
Agent ID
100
101
102
Agent First Name
Mike
Greg
Katherine
Agent Home Phone
553-3992
790-3992
551-4993
Date of Hire
05/16/95
10/15/95
03/01/96
Agent Last Name
Hernandez
Piercy
Ehrlich
Client ID
9001
9002
9003
Client First Name
Stewart
Shannon
Estela
Client Home Phone
553-3992
790-3992
551-4993
Client Last Name
Jameson
McLain
Pundt
Agent ID
100
101
102
......
......
......
......
Client ID
9003
9009
9001
Entertainer ID
3001
3000
3002
Start Time
1:00 PM
9:00 PM
3:00 PM
Engagement Date
04/01/96
04/13/96
05/02/96
Stop Time
3:30 PM
1:30 AM
6:00 PM
Entertainer ID
3000
3001
3002
Entertainer First Name
John
Mark
Teresa
Entertainer Last Name
Slade
Jebavy
Weiss
......
......
......
......
Agent ID
100
101
102
Agents
Clients
Entertainers
Engagements
Figure 1.5. Examples of related tables in a relational database.
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The Relational Database Model 15
can be associated with a record in the ENGAGEMENTS through match-
ing ENTERTAINER IDs.
As long as a user is familiar with the relationships among the tables in
the database, he can access data in an almost unlimited number of
ways. He can access data from tables that are directly related and from
tables that are indirectly related. Consider the Agents database in
Figure 1.5. Although the CLIENTS table is indirectly related to the
ENTERTAINERS table, the user can produce a list of clients and the
entertainers who have performed for them. (Of course, it really depends
on how the tables are actually structured, but I digress. This example
serves our purpose for now.) He can do this easily because CLIENTS is
directly related to ENGAGEMENTS and ENGAGEMENTS is directly re-
lated to ENTERTAINERS.
Retrieving Data
You retrieve data in a relational database by using Structured Query
Language (SQL). SQL is the standard language used to create, modify,
maintain, and query relational databases. Figure 1.6 shows a sample
SQL query statement you can use to produce a list of all clients in the
city of El Paso.
The three components of a basic SQL query are the SELECT…FROM
statement, the WHERE clause, and the ORDER BY clause. You use the
SELECT ClientLastName, ClientFirstName, ClientPhoneNumber FROM Clients WHERE City = “El Paso” ORDER BY ClientLastName, ClientFirstName;
Figure 1.6. A sample SQL query statement.
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16 Chapter 1 The Relational Database
SELECT clause to indicate the fields you want to use in the query and
the FROM clause to indicate the table(s) to which the fields belong. You
can filter the records the query returns by imposing criteria against
one or more fields with the WHERE clause, and then sort the results in
ascending or descending order with the ORDER BY clause.
Most of today’s major relational database software programs incorpo-
rate various forms of SQL implementations, ranging from windows in
which users can manually enter “raw” SQL statements to graphical
tools that allow users to build queries using various graphic elements.
For example, a user working with R:BASE Technologies’s R:BASE can
opt to build and execute SQL query statements directly from a com-
mand prompt, while someone using Microsoft Access may find it easier
to build queries using Access’s graphical query builder. Regardless of
how the queries are built, the user can save them for future use.
It’s not always necessary for you to know SQL in order to work with a
database. If your database software provides a graphical query builder
or you’re using a custom-built application to work with the data in
your database, you’ll never need to write a single SQL statement. It’s a
good idea, however, for you to gain a basic understanding of SQL. It
will help those of you using query-building tools to understand and
troubleshoot the queries you create with these tools, and it will defi-
nitely be to your advantage should you need to work high-end database
software programs, such as Oracle and Microsoft SQL Server.
❖ Note Although a detailed discussion of SQL is beyond the scope of this book, you should understand that SQL is a lan-
guage directly related to the relational database model. If you
have a desire or need to study SQL, you could start by reading
my second book, SQL Queries for Mere Mortals, and then move on
to any of the other SQL books that are on my recommended
reading list in Appendix G.
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The Relational Database Model 17
Advantages of a Relational Database
The relational database provides a number of advantages over previ-
ous models, such as the following:
• Built-in multilevel integrity: Data integrity is built into the model
at the field level to ensure the accuracy of the data; at the table
level to ensure that records are not duplicated and to detect
missing primary key values; at the relationship level to ensure
that the relationship between a pair of tables is valid; and at the
business level to ensure that the data is accurate in terms of the
business itself. (Integrity is discussed in detail as the design pro-
cess unfolds.)
• Logical and physical data independence from database applica-
tions: Neither changes a user makes to the logical design of the
database, nor changes a database software vendor makes to the
physical implementation of the database, will adversely affect the
applications built upon it.
• Guaranteed data consistency and accuracy: Data is consistent
and accurate due to the various levels of integrity you can impose
within the database. (This will become quite clear as you work
through the design process.)
• Easy data retrieval: At the user’s command, data can be retrieved
either from a particular table or from any number of related
tables within the database. This enables a user to view informa-
tion in an almost unlimited number of ways.
These and other advantages have proved beneficial to the business
community and to all those who need to collect and manage data.
Indeed, the relational database has become the database of choice in
many circumstances.
Until recently, one perceived disadvantage of the relational database
was that software programs based on it ran very slowly. This was not a
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18 Chapter 1 The Relational Database
fault of the relational model itself, but of the ancillary technology avail-
able at the time of the model’s introduction. Processing speed, memory,
and storage were simply insufficient to provide database software ven-
dors with a platform on which to build a full implementation of the
relational database, so the initial relational database software pro-
grams fell woefully short of their full potential. Since the early 1990s,
however, advances in both hardware technology and software engineer-
ing have made processing speed an insignificant issue and have
allowed vendors to make significant gains in their efforts to support the
model more fully.
You’ll learn more about the relational database model as you work
through the design process presented in this book. Some of the topics
you’ll encounter include creating tables, establishing data integrity,
working with relationships, and establishing business rules.
Relational Database Management Systems
A relational database management system (RDBMS) is a software pro-
gram you use to create, maintain, modify, and manipulate a relational
database. Many RDBMS programs also provide the tools you need to
create end-user applications that interact with the data stored in the
database. Of course, the quality of an RDBMS is a direct function of
the extent to which it supports the relational database model. Even
among “true” RDBMSs, support for the relational database varies
among vendors, and there is yet to be a full implementation of the rela-
tional model’s potential. Despite this, all RDBMS programs continue to
evolve and become more full-featured and powerful than ever before.
Since the early 1970s, a number of RDBMS programs have been pro-
duced by a variety of software vendors, encompassing various types of
computer hardware, operating systems, and programming environ-
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Relational Database Management Systems 19
ments. As we continue our voyage into the beginning of the twenty-first
century, it’s safe to say that RDBMS programs are as ubiquitous and
integrated into our daily lives as cellular phones.
In the earliest days of the relational database, RDBMSs were written for
use on mainframe computers. (Didn’t everything start on a main-
frame?) Two RDBMS programs prevalent in the early 1970s were
System R, developed by IBM at its San Jose Research Laboratory in
California, and Interactive Graphics Retrieval System (INGRES), devel-
oped at the University of California at Berkeley. These two programs
contributed greatly to the general appreciation of the relational model.
As the benefits of the relational database became more widely known,
many companies decided to make a slow move from hierarchical and
network database models to the relational database model, thus creat-
ing a need for more and better mainframe RDBMS programs. The
1980s saw the development of various commercial RDBMSs for main-
frame computers, such as Oracle, developed by Oracle Corporation,
and IBM’s DB2.
The early to mid-1980s saw the rise of the personal computer, and with
it the development of PC-based RDBMS programs. Some of the early
entries in this category, such as dBase by Ashton-Tate and FoxPro from
Fox Software, were nothing more than elementary file-based database-
management systems. True PC-based RDBMS programs began to
emerge with the introduction of R:BASE, originally developed by
Microrim, and Paradox, originally developed by Ansa Software. Each of
these products helped to spread the idea and potential of database
management from the mainframe-dominated domain of information
systems departments to the desktop of the common end user.
The need to share data became apparent as more and more users
worked with databases throughout the late 1980s and early 1990s. The
concept of a centrally located database that could be made available to
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20 Chapter 1 The Relational Database
multiple users seemed a very promising idea. This would certainly
make data management and database security much easier to imple-
ment. Database vendors responded to this need by developing client/
server RDBMS programs.
As Figure 1.7 illustrates, the data in this type of system resides on a
computer acting as a database server, and users interact with the data
through applications residing on their own computer, or database cli-
ent. The database developer uses the client/server RDBMS program to
create and maintain the database and attendant end-user application
programs. She implements data integrity and data security on the data-
base server, giving her the ability to base a variety of user applications
on the same set of data without affecting the data’s integrity or security.
Client/server RDBMS programs have been widely used for quite some
time to manage large volumes of shared data. Some of the more recent
entries in the client/server RDBMS category are Microsoft SQL Server
Server Client Client
Client
Client
Figure 1.7. A typical client/server architecture.
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Beyond the Relational Model 21
2000 from Microsoft Corporation and Oracle9i Application Server, from
Oracle Corporation.
Beyond the Relational Model
Although RDBMSs have been widely accepted for use in typical busi-
ness applications, such as inventory control, patient management,
banking, order processing, and event scheduling, they have proven to
be (currently, at least) lacking for such applications as computer-aided
design (CAD), geographic information systems (GIS), and multimedia
storage systems. Two new database models eventually emerged in
response to this problem: the object-oriented database and the object-
relational database.
The object-oriented model incorporates all of the characteristics of an
object-oriented programming language and essentially relegates the
relational database to the status of a data store. The fundamental idea
here is that the database developer handles every aspect of the data-
base, including the sets of operations that manipulate the data in the
database from within the object-oriented database programming soft-
ware. No longer is there a clear separation between the database
software and the application programming software. (As with any other
model, there are pros and cons to this approach.) Versant ODBMS by
Versant Corporation and UniData by IBM are two of the most recent
examples of object-oriented database software.
Unlike the relational model, which has a solid theoretical basis in two
distinct branches of mathematics, the object-oriented database model
has no specific theoretical foundation. As such, there is no singular,
cohesive consensus as to its definition. There is, however, a version of
the model proposed by the Object Management Group (OMG) that has
become somewhat of a de facto standard for object-oriented database-
management systems.
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22 Chapter 1 The Relational Database
The object-relational model (formerly known as the extended relational
data model), on the other hand, extended the relational database model
by incorporating various object-oriented elements and characteristics,
such as classes, encapsulation, and inheritance. The idea was that
these extensions would allow a relational database to manage and
manipulate more complex types of data, such as audio streams, video
clips, and architectural drawings. Though many in the database indus-
try believed this to be a move in the right direction, they still
maintained that it did not go far enough to deal with advanced data-
base applications. The model is still being refined and used, however,
as evidenced most recently by the entry of IBM’s IBM Informix Dynamic
Server 9.30.
Object-oriented supporters and relational database proponents are still
debating various issues to this day. Both sides agree that the rela-
tional database will not work for certain types of applications, but
disagree as to the appropriate solution to the problem. The issues are
quite complex and well beyond the scope of this work, but suffice it to
say that these debates are likely to go on until one side gives up or
technology renders them irrelevant.
What the Future Holds
The manner in which databases are used has evolved immensely in the
past several years. There came a time when many organizations began
❖ Note The OMG is a nonprofit international group that addresses the issues of object standards. It was founded in 1989
and comprises more than 800 member organizations. It is impor-
tant to note that the OMG is not a standards body, such as the
American National Standards Institute (ANSI), but merely an
advisory and certification group.
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What the Future Holds 23
to realize that there was a lot of useful information that could be gath-
ered from data they stored in various relational and nonrelational
databases. This prompted them to question whether there was a way to
mine the data for useful analytical information that they could then
use to make critical business decisions. Furthermore, they wondered if
they could consolidate and integrate their data into a viable knowledge-
base for their organizations. Indeed, these would be difficult questions
to answer.
IBM proposed the idea of a data warehouse, which, as originally con-
ceived, would allow organizations to access data stored in any number
of nonrelational databases. They were unsuccessful in their first
attempts at implementing data warehouses, primarily because of the
complexities and performance problems associated with such a task. It
has been only recently that the possibility of implementing a data ware-
house has become more viable and practical. Bill Inmon, widely
regarded as the father of the data warehouse, is a strong and vocal
advocate of the technology and has been instrumental in its evolution.
Data warehouses are now becoming more commonplace as companies
move to leverage the vast amounts of data they’ve stored in their data-
bases over the years.
The Internet has had a great influence on the way organizations use
databases. Many companies and businesses are using the Web to
expand their consumer base, and much of the data they share with
and gather from these consumers is stored in a database. The Inter-
net has even spawned a potentially viable solution to the problem of
consolidating data from various relational and nonrelational systems.
eXtensible Markup Language (XML) is quickly becoming a de facto
data transfer standard for sharing data across heterogeneous sys-
tems. It is platform- and system-agnostic, so a database system that
can write to and read from an XML document can share data with
other systems that can do the same. As the Internet continues to
become a dominant force in the world of business and commerce,
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24 Chapter 1 The Relational Database
more and more database vendors are rushing to incorporate XML
capabilities into their products.
A Final Note
RDBMSs now have a long history, and they continue to play a huge
role in the way people, businesses, and organizations interact with
their data. Their role is constantly expanding and evolving as data
becomes more accessible via the Internet and businesses move at an
ever-increasing pace to gain a presence on the Web. Numerous organi-
zations are heavily invested in their relational database systems, and
they are not likely to disappear anytime soon.
Summary
We opened this chapter by defining the two types of databases cur-
rently used in database management: operational databases and
analytical databases.
We then briefly discussed the hierarchical database model and the net-
work database model. Our discussion covered the data structures,
relationships, and data-access methods used in both models, as well as
their chief disadvantages. You learned that these models were widely
used in the early days of database management and led to the even-
tual development and introduction of the relational database model.
Next, we provided a detailed discussion of the relational database model,
its history, and its features. We noted that it is based on specific
branches of mathematics and that this mathematical foundation is what
❖ Note I’ve really only pricked the surface of XML; it does far more than I’ve suggested in this brief introduction.
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Summary 25
makes the model so structurally sound. Then we explored the model’s
data structures and relationships, and the role SQL plays in accessing
data within the model. You’ll remember, no doubt, that SQL is the stan-
dard language used to work with relational databases. We ended this
section by reviewing the advantages of the relational database model.
We then took a look at a brief history of relational database manage-
ment systems, beginning with the mainframe systems of the early
1970s and progressing through the PC-based systems of the 1980s to
the client/server systems of the 1990s. At this point you should have a
sense of the progression of circumstances that have led to the develop-
ment of the database systems we use today.
The chapter continued with a brief discussion of the object-relational
and object-oriented database models. Here you learned that these mod-
els emerged ostensibly as a means to deal with advanced database
applications, and that they each incorporate various object-oriented
elements and characteristics. You also learned that object-oriented
databases are still in a state of flux and that debates still continue
between object-oriented supporters and relational database propo-
nents over the viability of object-oriented solutions.
Finally, we closed the chapter with a brief discussion of data ware-
houses and XML. You learned that data warehouses are used to con-
solidate and integrate data from heterogeneous sources and that the
possibility of truly using them has only recently become more viable
and practical. Next, you learned that XML is quickly becoming a de
facto data transfer standard for sharing data across relational and non-
relational data sources. You also understand that relational databases
are likely to be used for quite some time, despite the great impact the
Internet has had on the way organizations use databases.
In the next chapter, we’ll discuss why you should be concerned with
database design and why theory is important. We’ll also cover the
objectives and advantages of good design.
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26 Chapter 1 The Relational Database
Review Questions
1. Name the two main types of databases in use today.
2. What type of data does an analytical database store?
3. True or False: An operational database is used primarily in on-line
transaction processing (OLTP) scenarios.
4. What two data models were commonly used in the days before the
relational database model?
5. Describe a parent/child relationship.
6. What is a set structure?
7. Name one of the branches of mathematics on which the relational
model is based.
8. How does a relational database store data?
9. Name the three types of relationships in a relational database.
10. How do you retrieve data in a relational database?
11. State two advantages of a relational database.
12. What is a relational database management system?
13. What is the premise behind the object-relational model?
14. What is the purpose of a data warehouse?
15. What is XML and why is it significant?
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27
2 Design Objectives
Everything factual is, in a sense, theory. The blue of the sky exhibits the basic laws of chromatics.
There is no sense in looking for something behind phenomena; they are theory.
—GOETHE
Topics Covered in This Chapter
Why Should You Be Concerned with Database Design?
The Importance of Theory
The Advantage of Learning a Good Design Methodology
Objectives of Good Design
Benefits of Good Design
Database-Design Methods
Summary
Review Questions
Why Should You Be Concerned with Database Design?
Some of you who work with RDBMS software programs may wonder
why you should be concerned with database design. After all, most
RDBMS programs come with sample databases that you can copy and
modify to suit your own needs, and you can even borrow tables from
the sample databases and use them in other databases that you’ve
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28 Chapter 2 Design Objectives
created. Some programs also provide tools that will guide you through
the process of defining and creating tables. However, these tools don’t
actually help you design a database—they merely help you create the
physical tables that you will include in the database.
What you must understand is that it’s better for you to use these tools
after you’ve created the logical database structure. RDBMS programs
provide the design tools and the sample databases to help minimize the
time it takes you to implement the database structure physically. Theo-
retically, reducing implementation time gives you more time to focus on
creating and building end-user applications.
Yet the primary reason you should be concerned with database design
is that it’s crucial to the consistency, integrity, and accuracy of the data
in a database. If you design a database improperly, it will be difficult for
you to retrieve certain types of information, and you’ll run the risk that
your searches will produce inaccurate information. Inaccurate informa-
tion is probably the most detrimental result of improper database
design—it can adversely affect your organization’s bottom line. In fact, if
your database affects the manner in which your business performs its
daily operations, or if it’s going to influence the future direction of your
business, you must be concerned with database design.
Let’s look at this from a different perspective for a moment: Think
about how you would go about having a custom home built for you.
What’s the first thing you’re going to do? Certainly you’re not going to
hire a contractor immediately and let him build your home however he
wishes. Surely you will first engage an architect to design your new
home and then hire a contractor to build it. The architect will explore
your needs and express them as a set of blueprints, recording deci-
sions about size and shape and requirements for various systems
(structural, mechanical, electrical). Next, the contractor will procure
the labor and materials, including the listed systems, and then assem-
ble them according to the drawings and specifications.
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The Importance of Theory 29
Now let’s return to our database perspective and think of the logical
database design as the architectural blueprints and the physical
database implementation as the completed home. The logical data-
base design describes the size, shape, and necessary systems for a
database; it addresses the informational and operational needs of
your business. You then build the physical implementation of the log-
ical database design, using your RDBMS software program. Once
you’ve created your tables, set up table relationships, and estab-
lished the appropriate levels of data integrity, your database is
complete. Now you’re ready to create applications that allow you to
interact easily with the data stored in the database, and you can be
confident that these applications will provide you with timely and,
above all, accurate information.
Although you can implement a poor design in an RDBMS, implement-
ing a good design is far more to your advantage because it will yield
accurate information, store data more efficiently and effectively, and
will be easier for you to manage and maintain.
The Importance of Theory
A number of major disciplines (and their associated design methodolo-
gies) have some type of theoretical basis. Structural engineers design
an unlimited variety of structures using the theories of physics. Com-
posers create beautiful symphonies and orchestral pieces using the
concepts found in music theory. The automobile industry uses aerody-
namics theories to design more fuel-efficient automobiles. The airplane
❖ Note In this chapter, I use the term theory to represent “gen- eral propositions used as principles” and not “conjectures or
proposals.”
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30 Chapter 2 Design Objectives
industry uses the same theories to design airplane wings that reduce
wind drag.
These examples demonstrate that theory is relevant and very impor-
tant. The chief advantage of theory is that it helps you predict out-
comes; it allows you to predict what will happen if you perform a
certain action or series of actions. You know if you drop a stone, it will
fall to the ground. If you are agile, you can get your toes out of the way
of Newton’s theory of gravity. The point is that it works every time. If
you chisel a stone flat and place it on another flat stone, you can pre-
dict that it will stay where you put it. This theory allows you to design
pyramids and cathedrals and brick outhouses. Now consider a data-
base example. Let’s assume you have a pair of tables that are related to
each other. You know that you can draw data from both tables simulta-
neously simply because of the way relational database theory works.
The data you draw from both tables is based on matching values of a
shared field between the tables themselves. Again, your actions have a
predictable result.
The relational database is based on two branches of mathematics
known as set theory and first-order predicate logic. This very fact is
what allows the relational database to guarantee accurate information.
These branches of mathematics also provide the basis for formulating
good design methodologies and the building blocks necessary to create
good relational database structures.
You might harbor an understandable reluctance to study complicated
mathematical concepts simply to carry out what seems to be a rather
limited task. You’re sure to hear claims that the mathematical theories
on which the relational database and its associated design methodolo-
gies are based don’t have any relevance to the real world, or that they
are somehow impractical. This is not true: Math is central to the rela-
tional model and is what guarantees the model’s viability. But cheer
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The Advantage of Learning a Good Design Methodology 31
up—it isn’t really necessary for you to know anything about set theory
or first-order predicate logic in order to use a relational database! You
certainly don’t have to know all the details of aerodynamics just to
drive an automobile. Aerodynamic theories may help you understand
and appreciate how an automobile can get better gas mileage, but they
won’t help you learn how to parallel park.
Mathematical theory provides the foundation for the relational database
model, and thus makes the model predictable, reliable, and sound. The-
ory describes the basic building blocks used to create a relational
database and provides guidelines for how it should be arranged. Arrang-
ing building blocks to achieve a desired result is defined as “design.”
The Advantage of Learning a Good Design Methodology
You could learn how to design a database properly by trial and error,
but it would take you a very long time, and you would probably have to
repair many mistakes along the way. The best approach is to learn a
good database-design methodology, such as the one in this book, and
then embark on designing your database.
You’ll gain several advantages from learning and using a good design
methodology.
• It gives you the skills you need to design a sound database struc-
ture. A large number of data-processing problems can be
attributed to the presence of redundant data, duplicate data, and
invalid data, or the absence of required data. All of these prob-
lems produce erroneous information and make certain queries
and reports difficult to run. You can avoid almost all of these
problems by employing a good design methodology.
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32 Chapter 2 Design Objectives
• It provides you with an organized set of techniques that will
guide you step-by-step through the design process. The organiza-
tion of the techniques enables you to make informed decisions
on every aspect of your design.
• It helps you keep your missteps and design reiterations to a mini-
mum. Of course, you will naturally make some mistakes when
you’re designing a database, but a good methodology helps you
recognize errors in your design and gives you the tools to correct
them. Additionally, the organization of the techniques within the
methodology keeps you from unnecessarily repeating a given
design process.
• It makes the design process easier and reduces the amount of time
you spend designing the database. You will inevitably waste valu-
able time taking an arbitrary trial-and-error approach to design
because it lacks the logic and organization that a good methodol-
ogy provides.
• It will help you understand and use your RDBMS software more
fully and effectively. As your knowledge of proper design expands
and grows, you’ll actually begin to understand why a given
RDBMS provides certain tools and how you can use them to
implement the structure within the RDBMS program.
Regardless of whether you use the design methodology presented in
this book or some other established methodology, you should choose a
design methodology, learn it as well as you can, and use it faithfully to
design your databases.
Objectives of Good Design
There are distinct objectives you must achieve in order to design a
good, sound database structure. You can avoid many of the problems
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Benefits of Good Design 33
mentioned in the previous section if you keep these objectives in mind
and constantly focus on them while you’re designing your database.
• The database supports both required and ad hoc information
retrieval. The database must store the data necessary to sup-
port information requirements defined during the design
process and any possible ad hoc queries that may be posed by
a user.
• The tables are constructed properly and efficiently. Each table
in the database represents a single subject, is composed of rela-
tively distinct fields, keeps redundant data to an absolute
minimum, and is identified throughout the database by a field
with unique values.
• Data integrity is imposed at the field, table, and relationship lev-
els. These levels of integrity help guarantee that the data
structures and their values will be valid and accurate at all times.
• The database supports business rules relevant to the organiza-
tion. The data must provide valid and accurate information that
is always meaningful to the business.
• The database lends itself to future growth. The database struc-
ture should be easy to modify or expand as the information
requirements of the business change and grow.
You might find it difficult at times to fulfill these objectives, but you’ll
certainly be pleased with your final database structure once you’ve met
them.
Benefits of Good Design
The time you invest in designing a sound database structure is time
well spent. Good design saves you time in the long run because you do
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34 Chapter 2 Design Objectives
not have to constantly revamp a quickly and poorly designed struc-
ture. You gain the following benefits when you apply good design
techniques:
• The database structure is easy to modify and maintain. Modifi-
cations you make to a field or table will not adversely affect
other fields or tables in the database.
• The data is easy to modify. Changes you make to the value of a
given field in a table will not adversely affect the values of other
fields within the table. Furthermore, a well-designed database
keeps duplicate fields to an absolute minimum, so you typically
modify a particular data value in one field only.
• Information is easy to retrieve. You’ll be able to create queries eas-
ily because the tables are well constructed and the relationships
between them are properly established.
• End-user applications are easy to develop and build. You can
spend more time on programming and addressing the data
manipulation tasks at hand, instead of working around the inevi-
table problems that arise when you work with a poorly designed
database.
Database-Design Methods
Traditional Design Methods
In general, traditional methods of database design incorporate three
phases: requirements analysis, data modeling, and normalization.
The requirements-analysis phase involves an examination of the busi-
ness being modeled, interviews with users and management to assess
the current system and to analyze future needs, and an assessment of
information requirements for the business as a whole. This process is
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Database-Design Methods 35
relatively straightforward, and, indeed, the design process presented in
this book follows the same line of thinking.
The data-modeling phase involves modeling the database structure us-
ing a data-modeling method, such as entity-relationship (ER) diagram-
ming, semantic-object modeling, or object-role modeling. Each of these
modeling methods provides a means of visually representing various
aspects of the database structure, such as the tables, table relation-
ships, and relationship characteristics. In fact, the modeling method
used in this book is a basic version of ER diagramming. Figure 2.1
shows an example of a basic ER diagram.
Each data-modeling method incorporates a set of diagramming sym-
bols used to represent a database’s structure and characteristics. For
example, the diagram in Figure 2.1 provides information on several
aspects of the database.
• The rectangles represent two tables called AGENTS and CLIENTS.
• The diamond represents a relationship between these two tables,
and the “1:N” within the diamond indicates that it is a one-to-
many relationship.
❖ Note I’ve incorporated the data-modeling method I use in this book into the design process itself rather than treating it sepa-
rately. I’ll introduce and explain each modeling technique as
appropriate throughout the process.
Agents 1:N Clients
Figure 2.1. An example of a basic ER diagram.
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36 Chapter 2 Design Objectives
• The vertical line next to the AGENTS table indicates that a client
must be associated with an agent, and the circle next to the CLI-
ENTS table indicates that an agent doesn’t necessarily have to be
associated with a client.
Fields are also defined and associated with the appropriate tables dur-
ing the data-modeling phase. Each table is assigned a primary key,
various levels of data integrity are identified and implemented, and
relationships are established via foreign keys. Once the initial table
structures are complete and the relationships have been established
according to the data model, the database is ready to go through the
normalization phase.
Normalization is the process of decomposing large tables into smaller
ones in order to eliminate redundant data and duplicate data and to
avoid problems with inserting, updating, or deleting data. During the
normalization process, table structures are tested against normal forms
and then modified if any of the aforementioned problems are found. A
normal form is a specific set of rules that can be used to test a table
structure to ensure that it is sound and free of problems. There are a
number of normal forms, and each one is used to test for a particular
set of problems. The normal forms currently in use are First Normal
Form, Second Normal Form, Third Normal Form, Fourth Normal Form,
Fifth Normal Form, Boyce-Codd Normal Form, and Domain/Key Nor-
mal Form.
The Design Method Presented in This Book
The design method that I use in this book is one that I’ve developed
over the years. It incorporates a requirements analysis and a simple
ER-diagramming method to diagram the database structure. However,
it does not incorporate the traditional normalization process or involve
the use of normal forms. The reason is simple: Normal forms can be
confusing to anyone who has not taken the time to study formal rela-
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Database-Design Methods 37
tional database theory. For example, examine the following definition of
Third Normal Form:
A relvar is in 3NF if and only if it is in 2NF and every non-key
attribute is nontransitively dependent on the primary key.1
This description is relatively meaningless to a reader who is unfamiliar
with the terms relvar, 3NF, 2NF, non-key attribute, transitively depen-
dent, and primary key.
The process of designing a database is not and should not be hard to
understand. As long as the process is presented in a straightforward
manner and each concept or technique is clearly explained, anyone
should be able to design a database properly. For example, the follow-
ing definition is derived from the results of using Third Normal Form
against a table structure, and I believe most people will find it clear and
easy to understand:
A table should have a field that uniquely identifies each of its
records, and each field in the table should describe the subject
that the table represents.
The process I used to formulate this definition is the same one I used
to develop my entire design methodology.
Back in the late 1980s, it occurred to me that the relational model had
been in existence for almost 20 years and that people had been designing
databases using the same basic methodology for about 12 years. I was
using the traditional design methodology at that time, but I occasionally
found it difficult to employ. The two things that bothered me the most
about it were the normalization process (as a whole) and the seemingly
endless iterations it took to arrive at a proper design. Of course, these
seemed to be sore points with most of the other database developers that
1. C. J. Date, An Introduction to Database Systems, 7th ed. (Boston, MA: Addison-Wesley, 2000), 362; emphasis added.
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38 Chapter 2 Design Objectives
I knew, so I certainly wasn’t alone in my frustrations. I thought about
these problems for quite some time, and then I came up with a solution.
I already knew that the purpose of normalization is to take an improp-
erly or poorly designed table and transform it into a table with a sound
structure. I also understood the process: Take a given table and test it
against the normal forms to determine whether it is properly designed.
If it isn’t designed properly, make the appropriate modifications, retest
it, and repeat the entire process until the table structure is sound. Fig-
ure 2.2 shows how I visualized the process at this point.
I kept these facts in mind and then posed the following questions:
1. If we assume that a thoroughly normalized table is properly and
efficiently designed, couldn’t we identify the specific characteris-
tics of such a table and state these to be the attributes of an ideal
table structure?
2. Couldn’t we then use that ideal table as a model for all tables we
create for the database throughout the design process?
Normalization Process
Non-normalized Tables
Normalized Tables
Figure 2.2. A graphic representation of the general normalization process.
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Database-Design Methods 39
The answer to both questions, of course, is yes, so I began in earnest to
develop the basis for my “new” design methodology. I first compiled dis-
tinct sets of guidelines for creating sound structures by identifying the
final characteristics of a well-defined database that successfully passed
the tests of each normal form. I then conducted a few tests, using the
new guidelines to create table structures for a new database and to
correct flaws in the table structures of an existing database. These
tests went very well, so I decided to apply this technique to the entire
traditional design methodology. I formulated guidelines to address
other issues associated with the traditional design method, such as
domains, subtypes, relationships, and referential integrity. After I com-
pleted the new guidelines, I performed more tests and found that my
methodology worked quite well.
The main advantage of my design methodology is that it removes many
aspects of the traditional design methodology that new database devel-
opers find intimidating. For example, normalization, in the traditional
sense, is now transparent to the developer because it has been incorpo-
rated (via the new guidelines) throughout the design process. Another
major advantage is that the methodology is clear and easy to imple-
ment. I believe much of this is due to the fact that I’ve written all the
guidelines in plain English, making them easy for most anyone to
understand.
It’s important for you to understand that this design methodology will
yield a fully normalized database structure only if you follow it as faith-
fully as you would any other design methodology. You cannot shortcut,
circumvent, de-emphasize, or omit any part of this methodology (or any
design methodology, for that matter) and expect to develop a sound
structure. You must go through the process diligently, methodically,
and completely in order reap the expected rewards.
There are a few basic terms you’ll have to learn before you delve into
the design process, and we’ll cover them in the next chapter.
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40 Chapter 2 Design Objectives
Summary
At the beginning of this chapter we looked at the importance of being
concerned with database design. You now understand that database
design is crucial to the integrity and consistency of the data contained
in a database. We have seen that the chief problem resulting from
improper or poor design is inaccurate information. Proper design is of
paramount concern because bad design can adversely affect the infor-
mation used by an organization.
Next, we entered into a discussion of the importance of theory, as well
as its relevance to the relational database model, and you learned that
the model’s foundation in mathematical theory makes it a very sound
and reliable structure.
Following this discussion, we looked at the advantages gained by learn-
ing a design methodology. Among other things, using a good
methodology yields an efficient and reliable database structure,
reduces the time it takes to design a database, and allows you to avoid
the typical problems caused by poor design.
Next, we listed the objectives of good design. Meeting these objectives is
crucial to the success of the database-design process because they help
you ensure that the database structure is sound. We then enumerated
the advantages of good design, and you learned that the time you
invest in designing a sound database structure is time well spent.
We closed this chapter with a short discussion of traditional database-
design methods and an explanation of the premise behind the design
method presented in this book. By now, you understand that tradi-
tional design methods are complex and can take some time to learn
and comprehend. On the other hand, the design method used in this
book is presented in a clear and straightforward manner, is easy to
implement, and will yield the same results as the traditional design
methodology.
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Review Questions 41
Review Questions
1. When is the best time to use an RDBMS program’s design tools?
2. True or False: Design is crucial to the consistency, integrity, and
accuracy of data.
3. What is the most detrimental result of improper database design?
4. What fact makes the relational database structurally sound and
able to guarantee accurate information?
5. State two advantages of learning a design methodology.
6. True or False: You will use your RDBMS program more effectively
if you understand database design.
7. State two objectives of good design.
8. What helps to guarantee that data structures and their values are
valid and accurate at all times?
9. State two benefits of applying good design techniques.
10. True or False: You can take shortcuts through some of the design
processes and still arrive at a good, sound design.
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3 Terminology
“When I use a word,” Humpty Dumpty said in rather a scornful tone, “it means just what I choose it to
mean—neither more nor less.” —LEWIS CARROLL
THROUGH THE LOOKING GLASS
Topics Covered in This Chapter
Why This Terminology Is Important
Value-Related Terms
Structure-Related Terms
Relationship-Related Terms
Integrity-Related Terms
Summary
Review Questions
The terms in this chapter are important for you to understand before
you embark upon learning the design process. Indeed, there are other
terms that you’ll need to learn, and I’ll cover them as you work through
the process. There’s also a glossary in the back of the book that you
can use to refresh your memory on any term you learn here or in the
following chapters.
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44 Chapter 3 Terminology
Why This Terminology Is Important
Relational database design has its own unique set of terms, just as any
other profession, trade, or discipline. Here are three good reasons why
it’s important for you to learn these terms.
1. They are used to express and define the special ideas and con-
cepts of the relational database model. Much of the terminology is
derived from the mathematical branches of set theory and first-
order predicate logic, which, as you already know, form the basis
of the relational database model.
2. They are used to express and define the database-design process
itself. The design process becomes clearer and much easier to
understand once you know these terms.
3. They are used anywhere a relational database or RDBMS is dis-
cussed. You’ll see these terms in publications such as trade
magazines, RDBMS software manuals, educational course materi-
als, and commercial RDBMS software books. You’ll also hear
these terms in conversations between various types of database
practitioners.
This chapter covers a majority of the terms used to define the ideas
and concepts of the design process, and each term is defined and dis-
cussed in some detail. (I provide pertinent details or necessary further
discussion for a given term at the point where the term is expressly
used within a specific technique in the design process.) There are sev-
eral other terms that I introduce and discuss later in the book because
they are more easily understood within the context of the specific idea
or concept to which they relate.
❖ Note The glossary contains concise definitions for all of the terms presented here and throughout the book.
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Value-Related Terms 45
There are four categories of terms defined in this chapter: value-related,
structure-related, relationship-related, and integrity-related.
Value-Related Terms
Data
The values you store in the database are data. Data is static in the
sense that it remains in the same state until you modify it by some
manual or automated process. Figure 3.1 shows some sample data.
On the surface, this data is meaningless. For example, there is no easy
way for you to determine what “92883” represents. Is it a zip code? Is it
a part number? Even if you know it represents a customer identifica-
tion number, is it one that is associated with George Edleman? There’s
just no way of knowing until you process the data.
Information
Information is data that you process in a manner that makes it mean-
ingful and useful to you when you work with it or view it. It is dynamic
in the sense that it constantly changes relative to the data stored in the
database, and also in the sense that it can be processed and presented
in an unlimited number of ways. You can show information as the
result of a SELECT statement, display it in a form on your computer
screen, or print it on paper as a report. The point to remember is that
you must process your data in some manner so that you can turn it into
meaningful information.
Figure 3.1. An example of basic data.
George Edleman 92883 05/16/96 95.00
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46 Chapter 3 Terminology
Figure 3.2 demonstrates how the data from the previous example can
be processed and transformed into information. It has been manipu-
lated in such a way—in this case as part of a patient invoice report—
that it is now meaningful to anyone who views it.
It is very important for you to understand the difference between data
and information. A database is designed to provide meaningful informa-
tion to someone within a business or organization. This information
can be provided only if the appropriate data exists in the database and
the database is structured in such a way as to support that informa-
tion. If you ever forget the difference between data and information, just
remember this little axiom:
Data is what you store; information is what you retrieve.
When you fully understand this single, simple concept, the logic behind
the database-design process will become crystal clear.
Figure 3.2. An example of data transformed into information.
Eastside Medical Clinic 7743 Kingman Dr. Seattle, WA 98032
(206) 555-9982
Patient Name: George Edelman Patient ID: 10884
Visit Date: 05/16/96 Physician: Daniel Chavez
Doctors Services Service Code Fee
X X
Consultation
EKG
Physical
Ultrasound
92883
92773
98377
97399
119.00
95.00
Nursing Services Service Code Fee
R.N. Exam
Supplies
Nurse Instruction
Insurance Report
89327
82372
88332
81368
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Value-Related Terms 47
Null
A null represents a missing or unknown value. You must understand
from the outset that a null does not represent a zero or a text string of
one or more blank spaces. The reasons are quite simple.
• A zero can have a very wide variety of meanings. It can represent
the state of an account balance, the current number of available
first-class ticket upgrades, or the current stock level of a particu-
lar product.
• Although a text string of one or more blank spaces is guaranteed
to be meaningless to most of us, it is definitely meaningful to a
query language like SQL. A blank space is a valid character as far
as SQL is concerned, and a character string composed of three
blank spaces (‘ ’) is just as legitimate as a character string
composed of three letters (‘abc’). In Figure 3.3, a blank repre-
sents the fact that Washington, D.C., is not located in any county
whatsoever.
• A zero-length string—two consecutive single quotes with no space
in between (‘‘)—is also an acceptable value to languages such as
SQL, and can be meaningful under certain circumstances. In an
EMPLOYEES table, for example, a zero-length string value in a
field called MIDDLEINITIAL may represent the fact that a particular
employee does not have a middle initial in his name.
❖ Note Unfortunately, data and information are two terms that are still frequently used interchangeably (and, therefore, errone-
ously) throughout the database industry. You’ll encounter this
error in numerous trade magazines and commercial database
books, and you’ll even see the terms misused by authors who
should know better.
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48 Chapter 3 Terminology
The Value of Nulls
A null is quite useful when you use it for its stated purpose, and the
CLIENTS table in Figure 3.3 clearly illustrates this. Each null in the
CLIENT COUNTY field represents a missing or unknown county name for
the record in which it appears. In order for you to use nulls correctly,
you must first understand why they occur at all.
Missing values are commonly the result of human error. For example,
consider the record for Shannon McLain. If you’re entering the data for
Ms. McLain and you fail to ask her for the name of the county she lives
in, that data is considered missing and is represented in the record as
a null. Once you recognize the error, however, you can correct it by
calling Ms. McLain and asking her for the county name.
❖ Note Due to space restrictions, I cannot always show all of the
fields for a given sample table. I will, however, show the fields
that are most relevant to the discussion at hand and use <<other
fields>> to represent fields that are unessential to the example.
You’ll see this convention in many examples throughout the
remainder of the book.
Figure 3.3. An example of a table containing null values.
Client ID
9001
9002
9003
Client First Name
Stewart
Shannon
Estela
Client City
Seattle
Poulsbo
Fremont
Client Last Name
Jameson
McLain
Pundt
Client County
King
Alameda
Clients
9004
9005
9006
Timothy
Marvin
Kendra
Bellevue
Washington
Portland
Ennis
Russo
Bonnicksen
King
State
WA
WA
CA
WA
DC
OR
<< other fields >>
......
......
......
......
......
......
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Value-Related Terms 49
Unknown values appear in a table for a variety of reasons. One reason
may be that a specific value you need for a field is as yet undefined. For
instance, you could have a CATEGORIES table in a School Scheduling
database that doesn’t currently contain a category for a new set of
classes that you want to offer beginning in the fall session. Another
reason a table might contain unknown values is that they are truly
unknown. Refer to the CLIENTS table in Figure 3.3 once again and
consider the record for Marvin Russo. Say that you’re entering the data
for Mr. Russo and you ask him for the name of the county he lives in. If
he doesn’t know the county name and you don’t happen to know the
county that includes the city in which he lives, then the value for the
county field in his record is truly unknown and is represented within
the record as a null. Obviously, you can correct the problem once
either of you determines the correct county name.
A field value may also be null if none of its values applies to a particular
record. Assume for a moment that you’re working with an EMPLOYEES
table that contains a SALARY field and a HOURLYRATE field. The value for
one of these two columns is always going to be null because an employee
cannot be paid both a fixed salary and an hourly rate.
It’s important to note that there is a very slim difference between “does
not apply” and “is not applicable.” In the previous example, the value of
one of the two fields literally does not apply. Now assume you’re work-
ing with a PATIENTS table that contains a field called HAIRCOLOR and
you’re currently updating a record for an existing male patient. If that
patient recently became bald, then the value for that field is definitely
“not applicable.” Although you could just use a null to represent a
value that is not applicable, I always recommend that you use a true
value such as “N/A” or “Not Applicable.” This will make the informa-
tion clearer in the long run.
As you can see, whether you allow nulls in a table depends on the
manner in which you’re using the data. Now that we’ve shown you the
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50 Chapter 3 Terminology
positive side of using nulls, let’s take a look at the negative implication
of using them.
The Problem with Nulls
The major disadvantage of nulls is that they have an adverse effect on
mathematical operations. An operation involving a null evaluates to
null. This is logically reasonable—if a number is unknown then the
result of the operation is necessarily unknown. Note how a null alters
the outcome of the operation in the following example:
(25 × 3) + 4 = 79
(Null × 3) + 4 = Null
(25 × Null) + 4 = Null
(25 × 3) + Null = Null
The PRODUCTS table in Figure 3.4 helps to illustrate the effects nulls
have on mathematical expressions that incorporate fields from a table.
In this case, the value for the TOTAL VALUE field is derived from the
mathematical expression “[SRP] × [QTY ON HAND].” As you inspect the records in this table, note that the value for the TOTAL VALUE field is
missing where the QTY ON HAND value is null, resulting in a null value
for the TOTAL VALUE field as well. This leads to a serious undetected error
that occurs when all the values in the TOTAL VALUE field are added
together: an inaccurate total. This error is “undetected” because an
RDBMS program will not inherently alert you of the error. The only way
to avoid this problem is to ensure that the values for the QTY ON HAND
field cannot be null.
Figure 3.5 helps to illustrate the effect nulls have on aggregate func-
tions that incorporate the values of a given field in a table. The result of
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Value-Related Terms 51
an aggregate function, such as COUNT(<fieldname>), will be null if it is
based on a field that contains null values. The table in Figure 3.5 shows
the results of a summary query that counts the total number of occur-
rences of each category in the PRODUCTS table shown in Figure 3.4.
The value of the TOTAL OCCURRENCES field is the result of the function ex-
pression COUNT([CATEGORY]). Notice that the summary query shows “0”
occurrences of an unspecified category, implying that each product has
been assigned a category. This information is clearly inaccurate be-
cause there are two products in the PRODUCTS table that have not
been assigned a category.
Figure 3.4. The nulls in this table will have an effect on mathematical opera- tions involving the table’s fields.
Products
Category
Accessories
Accessories
Components
Bikes
SRP
75.00
65.00
36.00
23.50
1,200.00
7.45
Qty On Hand
20
33
16
10
Total Value
1,300.00
1,118.00
376.00
74.50
Product ID
70001
70002
70003
70004
70005
70006
Product Description
Shur-Lok U-Lock
SpeedRite Cyclecomputer
SteelHead Microshell Helmet
SureStop 133-MB Brakes
Diablo ATM Mountain Bike
UltraVision Helmet Mount Mirrors
Figure 3.5. Nulls affect the results of an aggregate function.
Total Occurrences
0
2
1
1
Category
Accessories
Bikes
Components
Category Summary
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52 Chapter 3 Terminology
The issues of missing values, unknown values, and whether a value
will be used in a mathematical expression or aggregate function are all
taken into consideration in the database-design process, and we will
revisit and discuss these issues further in later chapters.
Structure-Related Terms
Table
According to the relational model, data in a relational database is
stored in relations, which are perceived by the user as tables. Each
relation is composed of tuples (records) and attributes (fields).
Figure 3.6 shows a typical table structure.
Tables are the chief structures in the database and each table always
represents a single, specific subject. The logical order of records and
fields within a table is of absolutely no importance, and every table
contains at least one field—known as a primary key—that uniquely
Figure 3.6. A typical table structure.
Client ID
9001
9002
9003
Client First Name
Stewart
Shannon
Estela
Client City
Seattle
Poulsbo
Tacoma
Client Last Name
Jameson
McLain
Pundt
Clients
9004
9005
9006
Timothy
Marvin
Kendra
Seattle
Bellingham
Tacoma
Ennis
Russo
Bonnicksen
Records
Fields
<< other fields >>
......
......
......
......
......
......
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Structure-Related Terms 53
identifies each of its records. (In Figure 3.6, for example, CLIENT ID is
the primary key of the CLIENTS table.) In fact, data in a relational
database can exist independently of the way it is physically stored in
the computer because of these last two table characteristics. This is
great news for the user because he or she isn’t required to know the
physical location of a record in order to retrieve its data.
The subject that a given table represents can either be an object or
event. When the subject is an object, it means that the table repre-
sents something that is tangible, such as a person, place, or thing.
Regardless of its type, every object has characteristics that can be
stored as data. This data can then be processed in an almost infinite
number of ways. Pilots, products, machines, students, buildings, and
equipment are all examples of objects that can be represented by a
table, and Figure 3.6 illustrates one of the most common examples of
this type of table.
When the subject of a table is an event, it means that the table repre-
sents something that occurs at a given point in time having
characteristics you wish to record. These characteristics can be stored
as data and then processed as information in exactly the same man-
ner as a table that represents some specific object. Examples of events
you may need to record include judicial hearings, distributions of
funds, lab test results, and geological surveys. Figure 3.7 shows an
example of a table representing an event that we all have experienced
at one time or another—a doctor’s appointment.
A table that stores data used to supply information is called a data
table, and it is the most common type of table in a relational database.
Data in this type of table is dynamic because you can manipulate it
(modify, delete, and so forth) and process it into information in some
form or fashion. You’ll constantly interact with these types of tables as
you work with your database.
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54 Chapter 3 Terminology
A validation table (also known as a lookup table), on the other hand,
stores data that you specifically use to implement data integrity. A vali-
dation table usually represents subjects, such as city names, skill
categories, product codes, and project identification numbers. Data in
this type of table is static because it will very rarely change at all.
Although you have very little direct interaction with these tables, you’ll
frequently use them indirectly to validate values that you enter into a
data table. Figure 3.8 shows an example of a validation table.
I’ll discuss validation tables in more detail in Chapter 11.
Figure 3.7. A table representing an event.
Patient Visit
Visit Date
05/01/96
05/01/96
05/02/96
05/02/96
05/02/96
05/03/96
Blood Pressure
120/80
112/74
120/80
160/90
110/75
120/80
Visit Time
10:30
13:00
09:30
11:00
14:00
09:30
Patient ID
92001
97002
99014
96105
96203
98003
Physician
Hernandez
Piercy
Rolson
Hernandez
Hernandez
Rolson
<< other fields >>
......
......
......
......
......
......
Figure 3.8. An example of a validation table.
Category Name
Accessories
Bikes
Clothing
Components
Category ID
10000
20000
30000
40000
Categories
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Structure-Related Terms 55
Field
A field (known as an attribute in relational database theory) is the
smallest structure in the database and it represents a characteristic of
the subject of the table to which it belongs. Fields are the structures
that actually store data. The data in these fields can then be retrieved
and presented as information in almost any configuration that you can
imagine. The quality of the information you get from your data is in
direct proportion to the amount of time you’ve dedicated to ensuring
the structural integrity and data integrity of the fields themselves.
There is just no way to underestimate the importance of fields.
Every field in a properly designed database contains one and only one
value, and its name will identify the type of value it holds. This makes
entering data into a field very intuitive. If you see fields with names
such as FIRSTNAME, LASTNAME, CITY, STATE, and ZIPCODE, you know
exactly what type of values go into each field. You’ll also find it very
easy to sort the data by state or look for everyone whose last name is
“Hernandez.”
You’ll typically encounter three other types of fields in an improperly or
poorly designed database.
1. A multipart field (also known as a composite field), which contains
two or more distinct items within its value.
2. A multivalued field, which contains multiple instances of the same
type of value.
3. A calculated field, which contains a concatenated text value or the
result of a mathematical expression.
Figure 3.9 shows a table with an example of each of these types of
fields.
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56 Chapter 3 Terminology
I’ll cover calculated, multipart, and multivalued fields in greater detail
in Chapter 7.
Record
A record (known as a tuple in relational database theory) represents a
unique instance of the subject of a table. It is composed of the entire
set of fields in a table, regardless of whether or not the fields contain
values. Because of the manner in which a table is defined, each record
is identified throughout the database by a unique value in the primary
key field of that record.
In Figure 3.9, each record represents a unique client within the table,
and the CLIENT ID field is used to identify a given client throughout the
database. In turn, each record includes all of the fields within the table,
and each field describes some aspect of the client represented by the
record. Consider the record for Timothy Ennis, for example. His record
represents a unique instance of the table’s subject (“Clients”) and
includes the total collection of fields in the table, treated as a unit. The
Figure 3.9. A table containing regular, calculated, multipart, and multivalued fields.
Clients
Calculated Field Multipart Field Multivalued Field
Client ID
9001
9002
9003
9004
9005
9006
Client First Name
Stewart
Shannon
Estela
Timothy
Marvin
Kendra
Client Last Name
Jameson
McLain
Pundt
Ennis
Russo
Bonnicksen
Client City, State, Zip
Seattle, WA 98125
Poulsbo, WA 98370
Bellevue, WA 98005
Seattle, WA 98115
Bellingham, WA 98225
Olympia, WA 98504
Client Full Name
Stewart Jameson
Shannon McLain
Estela Pundt
Timothy Ennis
Marvin Russo
Kendra Bonnicksen
Address
......
......
......
......
......
......
Account Rep
John, Sandi
Frits
John
Frits, Sandi
Frits, John
Sandi
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Structure-Related Terms 57
values of those fields represent relevant facts about Mr. Ennis that are
important to someone in the organization.
Records are a key factor in understanding table relationships because
you’ll need to know how a record in one table relates to other records
in another table.
View
A view is a “virtual” table composed of fields from one or more tables in
the database; the tables that comprise the view are known as base
tables. The relational model refers to a view as “virtual” because it
draws data from base tables rather than storing data on its own. In
fact, the only information about a view that is stored in the database is
its structure. Many major RDBMS programs support views, but some
(such as Microsoft Access) refer to them as saved queries. Your specific
RDBMS program will determine whether you refer to this object as a
query or a view.
Views enable you to see the information in your database from many
different aspects, providing you with a great amount of flexibility when
you work with your data. You can create views in a variety of ways and
they are especially useful when you base them on multiple related
tables. In a school scheduling database, for example, you could create
a view that consolidates data from the STUDENTS, CLASSES, and
CLASS SCHEDULES tables.
Figure 3.10 shows a view called INSTRUMENT ASSIGNMENTS that is
composed of fields taken from the STUDENTS, INSTRUMENTS, and
STUDENT INSTRUMENTS tables. The view displays data that it draws
from all of these tables simultaneously, based on matching values
between the STUDENT ID fields in the STUDENTS and STUDENT
INSTRUMENTS tables, and the INSTRUMENT ID fields in the INSTRU-
MENTS and STUDENT INSTRUMENTS tables.
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58 Chapter 3 Terminology
There are three major reasons that views are important.
1. They allow you to work with data from multiple tables simulta-
neously. (In order for a view to do this, the tables must have
connections, or relationships, to each other.)
2. They enable you to prevent certain users from viewing or manipu-
lating specific fields within a table or group of tables. This
capability can be very advantageous in terms of security.
3. You can use them to implement data integrity. A view you use for
this purpose is known as a validation view.
You’ll learn more about designing and using views in Chapter 12.
Figure 3.10. An example of a typical view.
Student Instruments
Student ID
60002
60003
60001
Checkout Date
09/26/01
09/28/01
09/28/01
Instrument ID
1003
1002
1000
Instruments
Instrument ID Instrument Description Category << other fields >>
......
......
......
1000 Stratocaster Guitar
1002 JCM 2000 Tube Super Lead Amplifier
1003 Twin Reverb Reissue Amplifier
1001 Player 2100 Multieffects Multieffect Unit
......
Student Phone
553-3992
790-3992
551-4993
Student Last Name
Erlich
McLain
Rosales
Student First Name
Zachary
Susan
Joe
Student ID
60001
60002
60003
Students
<< other fields >>
......
......
......
Instrument Assignments (View)
Student Last Name
Erlich
McLain
Rosales
Student First Name
Zachary
Susan
Joe
Checkout Date
09/26/01
09/28/01
09/28/01
Instrument Description
Stratocaster
JCM 2000 Tube Super Lead
Twin Reverb Reissue
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Structure-Related Terms 59
Keys
Keys are special fields that play very specific roles within a table, and
the type of key determines its purpose within the table. There are sev-
eral types of keys a table may contain, but the two most significant
ones are the primary key and the foreign key.
A primary key is a field or group of fields that uniquely identifies each
record within a table; if a primary key is composed of two or more
fields, it is known as a composite primary key. The primary key is abso-
lutely the most important key in the entire table.
• A primary key value identifies a specific record throughout the entire database,
• The primary key field identifies a given table throughout the entire database.
• The primary key enforces table-level integrity and helps estab-
lish relationships with other tables in the database. (You’ll learn
more about relationships in the next section.)
Every table in your database should have a primary key!
❖ Note Although every major database vendor supports the type of view I’ve described in this section, several vendors are now
supporting what is known as an indexed (or materialized) view.
An indexed view is different from a “regular” view in that it does
store data, and its fields can be indexed to improve the speed at
which the RDBMS processes the view’s data. A full discussion of
indexed views is beyond the scope of this book because it is a
vendor-specific implementation issue. However, you should
research this topic further if you are working with a client/server
or mainframe RDBMS program.
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60 Chapter 3 Terminology
The AGENT ID field in Figure 3.11 is a good example of a primary key. It
uniquely identifies each agent within the AGENTS table and helps to
guarantee table-level integrity by ensuring nonduplicate records. It can
also be used to establish relationships between the AGENTS table and
other tables in the database, such as the ENTERTAINERS table shown
in the example.
When you determine that two tables bear a relationship to each other,
you typically establish the relationship by taking a copy of the primary
key from the first table and incorporating it into the structure of the
second table, where it becomes a foreign key. The name “foreign key” is
derived from the fact that the second table already has a primary key of
its own, and the primary key you are introducing from the first table is
“foreign” to the second table.
Figure 3.11 also shows a good example of a foreign key. Note that AGENT
ID is the primary key of the AGENTS table and a foreign key in the
Figure 3.11. An example of primary and foreign key fields.
Agents
Agent ID
100
101
102
Agent First Name
Stella
Steve
Randi
Agent Last Name
Rosales
Pundt
Nathanson
Date of Hire
05/16/95
10/15/95
03/01/96
Agent Home Phone
553-3992
790-3992
551-4993
Primary Key
Primary Key
Foreign Key
Entertainers
Entertainer Phone
555-9928
959-8837
709-3542
Entertainer Name
Jazz Time
The Mike Hernandez Trio
The Country Squires
Agent ID
100
101
100
Entertainer ID
9001
9002
9003
<< other fields >>
......
......
......
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Structure-Related Terms 61
ENTERTAINERS table. AGENT ID assumes this role because the ENTER-
TAINERS table already has a primary key—ENTERTAINER ID. As such,
AGENT ID establishes the relationship between both of the tables.
Besides helping to establish relationships between pairs of tables, for-
eign keys also help implement and ensure relationship-level integrity.
This means that the records in both tables will always be properly
related because the values of a foreign key must match existing values
of the primary key to which it refers. Relationship-level integrity also
helps you avoid the dreaded “orphaned” record, a classic example of
which is an order record without an associated customer. If you don’t
know who made the order, you can’t process it, and you obviously can’t
invoice it. That’ll throw your quarterly sales off!
Key fields play an important part in a relational database, and you
must learn how to create and use them. You’ll learn more about pri-
mary keys in Chapters 8 and 10.
Index
An index is a structure an RDBMS provides to improve data process-
ing. Your particular RDBMS program will determine how the index
works and how you use it. However, an index has absolutely nothing
to do with the logical database structure! The only reason I include the
term index in this chapter is that people often confuse it with the
term key.
Index and key are just two more terms that are widely and frequently
misused throughout the database industry and in numerous database-
related publications. (Remember my comments on data and informa-
tion?) You’ll always know the difference between the two if you
remember that keys are logical structures you use to identify records
within a table, and indexes are physical structures you use to optimize
data processing.
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62 Chapter 3 Terminology
Relationship-Related Terms
Relationships
A relationship exists between two tables when you can in some way
associate the records of the first table with those of the second. You
can establish the relationship via a set of primary and foreign keys (as
you learned in the previous section) or through a third table known as
a linking table (also known as an associative table). The manner in
which you establish the relationship really depends on the type of rela-
tionship that exists between the tables. (You’ll learn more about that in
a moment.) Figure 3.11 illustrates a relationship established via pri-
mary/foreign keys, and Figure 3.12 illustrates a relationship
established with a linking table.
Figure 3.12. A relationship established between two tables with the help of a linking table.
Student Phone
553-3992
790-3992
551-4993
Student Last Name
Erlich
McLain
Rosales
Student First Name
Zachary
Susan
Joe
Student ID
60001
60002
60003
Students
Class Name
Intro. to Political Science
Adv. Music Theory
American History
Class ID
900001
900002
900003
Instructor ID
220087
220039
220148
Classes
Student Schedule (Linking Table )
Student ID
60003
60001
60003
60002
60001
Class ID
900001
900003
900003
900002
900001
<< other fields >>
......
......
......
<< other fields >>
......
......
......
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Relationship-Related Terms 63
A relationship is an important component of a relational database.
• It enables you to create multitable views.
• It is crucial to data integrity because it helps reduce redundant
data and eliminate duplicate data.
You can characterize every relationship in three ways: by the type of
relationship that exists between the tables, the manner in which each
table participates, and the degree to which each table participates.
Types of Relationships
There are three specific types of relationship (traditionally known as a
cardinality) that can exist between a pair of tables: one-to-one, one-to-
many, and many-to-many.
One-to-One Relationships
A pair of tables bears a one-to-one relationship when a single record in
the first table is related to only one record in the second table, and a
single record in the second table is related to only one record in the first
table. In this type of relationship, one table serves as a “parent” table
and the other serves as a “child” table. You establish the relationship by
taking a copy of the parent table’s primary key and incorporating it
within the structure of the child table, where it becomes a foreign key.
This is a special type of relationship because it is the only one in which
both tables may actually share the same primary key.
Figure 3.13 shows an example of a typical one-to-one relationship. In
this case, EMPLOYEES is the parent table and COMPENSATION is the
child table. The relationship between these tables is such that a single
record in the EMPLOYEES table can be related to only one record in the
COMPENSATION table, and a single record in the COMPENSATION
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64 Chapter 3 Terminology
table can be related to only one record in the EMPLOYEES table. Note
that EMPLOYEE ID is indeed the primary key in both tables. However, it
will also serve the role of a foreign key in the child table.
One-to-Many Relationships
A one-to-many relationship exists between a pair of tables when a sin-
gle record in the first table can be related to many records in the
second table, but a single record in the second table can be related to
only one record in the first table. (The parent/child model I used to
describe a one-to-one relationship works here as well. In this case, the
table on the “one” side of the relationship is the parent table, and the
table on the “many” side is the child table.) You establish a one-to-
many relationship by taking a copy of the parent table’s primary key
and incorporating it within the structure of the child table, where it
becomes a foreign key.
Figure 3.13. An example of a one-to-one relationship.
Employees
Compensation
Home Phone
553-3992
790-3992
551-4993
Employee Last Name
Erlich
McLain
Rosales
Employee First Name
Zachary
Susan
Joe
Employee ID
100
101
102
<< other fields >>
......
......
......
Employee ID
100
Commission Rate
5.0%
Hourly Rate
25.00
<< other fields >>
......
101 3.5%19.75 ......
102 5.0%22.50 ......
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Relationship-Related Terms 65
The example in Figure 3.14 illustrates a typical one-to-many relation-
ship. A single record in the AGENTS table can be related to one or more
records in the ENTERTAINERS table, but a single record in the EN-
TERTAINERS table is related to only one record in the AGENTS table.
As you probably have already guessed, AGENT ID is a foreign key in the
ENTERTAINERS table.
This is by far the most common relationship that exists between a pair
of tables in a database. It is crucial from a data-integrity standpoint
because it helps to eliminate duplicate data and to keep redundant
data to an absolute minimum.
Many-to-Many Relationships
A pair of tables bears a many-to-many relationship when a single
record in the first table can be related to many records in the second
table and a single record in the second table can be related to many
Figure 3.14. An example of a one-to-many relationship.
Entertainers
Entertainer Phone
709-3542
Entertainer Name
The Country Squires
Agent ID
100
Entertainer ID
9003
<< other fields >>
......
......
......
555-9928Jazz Time1019001
959-8837The Mike Hernandez Trio1009002
Agents
Agent ID
100
101
102
Agent First Name
Stella
Steve
Randi
Agent Last Name
Rosales
Pundt
Nathanson
Date of Hire
05/16/95
10/15/95
03/01/96
Agent Home Phone
553-3992
790-3992
551-4993
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66 Chapter 3 Terminology
records in the first table. You establish this relationship with a linking
table. (You learned a little bit about this type of table at the beginning
of this section.) A linking table makes it easy for you to associate
records from one table with those of the other and will help to ensure
that you have no problems adding, deleting, or modifying related data.
You define a linking table by taking copies of the primary key of each
table in the relationship and using them to form the structure of the
new table. These fields actually serve two distinct roles: Together, they
form the composite primary key of the linking table; separately, they
each serve as a foreign key.
A many-to-many relationship that is not properly established is “unre-
solved.” Figure 3.15 shows a classic and clear example of an unre-
solved many-to-many relationship. In this instance, a single record in
the STUDENTS table can be related to many records in the CLASSES
table and a single record in the CLASSES table can be related to many
records in the STUDENTS table.
Figure 3.15. An example of an unresolved many-to-many relationship.
Student Phone
553-3992
790-3992
551-4993
Student Last Name
Erlich
McLain
Rosales
Student First Name
Zachary
Susan
Joe
Student ID
60001
60002
60003
Students
<< other fields >>
......
......
......
Class Name
Intro. to Political Science
Adv. Music Theory
American History
Class ID
900001
900002
900003
Instructor ID
220087
220039
220148
Classes
<< other fields >>
......
......
......
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Relationship-Related Terms 67
This relationship is unresolved due to the inherent peculiarity of the
many-to-many relationship. The main issue is this: How do you easily
associate records from the first table with records in the second table?
To reframe the question in terms of the tables shown in Figure 3.15,
how do you associate a single student with several classes or a specific
class with several students? Do you insert a few STUDENT fields into the
CLASSES table? Or do you add several CLASS fields to the STUDENTS
table? Either of these approaches will make it difficult for you to work
with the data and will affect data integrity adversely. The best approach
for you to take is to create and use a linking table, which will resolve
the many-to-many relationship in the most appropriate and effective
manner. Figure 3.16 shows this solution in practice.
Figure 3.16. Resolving the many-to-many relationship with a linking table.
Student Phone
553-3992
790-3992
551-4993
Student Last Name
Erlich
McLain
Rosales
Student First Name
Zachary
Susan
Joe
Student ID
60001
60002
60003
Students
Class Name
Intro. to Political Science
Adv. Music Theory
American History
Class ID
900001
900002
900003
Instructor ID
220087
220039
220148
Classes
Student Schedule (Linking Table )
Student ID
60003
60001
60003
60002
60001
Class ID
900001
900003
900003
900002
900001
<< other fields >>
......
......
......
<< other fields >>
......
......
......
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68 Chapter 3 Terminology
It’s important for you to know the type of relationship that exists
between a pair of tables because it determines how the tables are
related, whether or not records between the tables are interdependent,
and the minimum and maximum number of related records that can
exist within the relationship. You’ll learn much more about relation-
ships in Chapter 10.
Types of Participation
A table’s participation within a relationship can be either mandatory or
optional. Say there is a relationship between two tables called TABLE_A
and TABLE_B.
• TABLE_A’s participation is mandatory if you must enter at least
one record into TABLE_A before you can enter records into
TABLE_B.
• TABLE_A’s participation is optional if you are not required to
enter any records into TABLE_A before you can enter records
into TABLE_B.
Let’s take a look at an example using the AGENTS and CLIENTS tables
in Figure 3.17. The AGENTS table has a mandatory participation within
the relationship if an agent must exist before a new client can be
entered into the CLIENTS table. However, the AGENTS table’s partici-
pation is optional if there is no requirement for an agent to exist in the
table before a new client can be entered into the CLIENTS table. You
can identify the appropriate type of participation for the AGENTS table
by determining the way its data is being used in relation to the data in
the CLIENTS table. For example, when you want to ensure that each
client is assigned to an available agent, you make the AGENTS table’s
participation within the relationship mandatory.
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Relationship-Related Terms 69
Degree of Participation
The degree of participation determines the minimum number of records
that a given table must have associated with a single record in the
related table and the maximum number of records that a given table is
allowed to have associated with a single record in the related table.
Consider, once again, a relationship between two tables called
TABLE_A and TABLE_B. You establish the degree of participation for
TABLE_B by indicating a minimum and maximum number of records
in TABLE_B that can be related to a single record in TABLE_A. If a sin-
gle record in TABLE_A can be related to no fewer than 1 but no more
than 10 records in TABLE_B, then the degree of participation for
TABLE_B is 1,10. (The degree of participation is notated with the mini- mum number on the left and the maximum number on the right,
Figure 3.17. The AGENTS and CLIENTS tables.
Agents
Clients
Agent ID
100
101
102
Agent First Name
Stella
Steve
Randi
Agent Last Name
Rosales
Pundt
Nathanson
Date of Hire
05/16/95
10/15/95
03/01/96
Agent Home Phone
553-3992
790-3992
551-4993
Client Home Phone
553-3992
790-3992
551-4993
Client Last Name
Jameson
McLain
Barker
Client First Name
Stewart
Shannon
Scott
Agent ID
100
101
102
Client ID
9001
9002
9003
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70 Chapter 3 Terminology
separated by a comma.) You can establish the degree of participation
for TABLE_A in the same manner. You can identify the degree of partic-
ipation for each table in a relationship by determining the way the data
in each table is related and how the data is being used.
Let’s consider the AGENTS and CLIENTS tables in Figure 3.17 once
more. If you require an agent to handle at least one client, but cer-
tainly no more than eight, then the degree of participation for the
CLIENTS table is 1,8. When you want to ensure that a client can only be assigned to one agent, then you indicate the degree of participation
for the AGENTS table as 1,1.
Integrity-Related Terms
Field Specification
A field specification (traditionally known as a domain) represents all the
elements of a field. Each field specification incorporates three types of
elements: general, physical, and logical.
• General elements constitute the most fundamental information
about the field and include items such as Field Name, Descrip-
tion, and Parent Table.
• Physical elements determine how a field is built and how it is
represented to the person using it. This category includes items
such as Data Type, Length, and Display Format.
• Logical elements describe the values stored in a field and include
items such as Required Value, Range of Values, and Default
Value.
You’ll learn all of the elements associated with a field specification,
including those mentioned here, in Chapter 9.
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Integrity-Related Terms 71
Data Integrity
Data integrity refers to the validity, consistency, and accuracy of the
data in a database. I cannot overstate the fact that the level of accu-
racy of the information you retrieve from the database is in direct
proportion to the level of data integrity you impose upon the database.
Data integrity is one of the most important aspects of the database-
design process, and you cannot underestimate, overlook, or even par-
tially neglect it. To do so would put you at risk of being plagued by
errors that are very hard to detect or identify. As a result, you would be
making important decisions on information that is inaccurate at best,
or totally invalid at worst.
There are four types of data integrity that you’ll implement during the
database-design process. Three types of data integrity are based on
various aspects of the database structure and are labeled according to
the area (level) in which they operate. The fourth type of data integrity
is based on the way an organization perceives and uses its data. The
following is a brief description of each:
1. Table-level integrity (traditionally known as entity integrity)
ensures that there are no duplicate records within the table and
that the field that identifies each record within the table is unique
and never null.
2. Field-level integrity (traditionally known as domain integrity)
ensures that the structure of every field is sound; that the values
in each field are valid, consistent, and accurate; and that fields of
the same type (such as CITY fields) are consistently defined
throughout the database.
3. Relationship-level integrity (traditionally known as referential integ-
rity) ensures that the relationship between a pair of tables is
sound and that the records in the tables are synchronized when-
ever data is entered into, updated in, or deleted from either table.
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72 Chapter 3 Terminology
4. Business rules impose restrictions or limitations on certain
aspects of a database based on the ways an organization per-
ceives and uses its data. These restrictions can affect aspects of
database design, such as the range and types of values stored in a
field, the type of participation and the degree of participation of
each table within a relationship, and the type of synchronization
used for relationship-level integrity in certain relationships. All of
these restrictions are discussed in more detail in Chapter 11.
Because business rules affect integrity, they must be considered
along with the other three types of data integrity during the design
process.
Summary
This chapter began with an explanation of why terminology is impor-
tant for defining, discussing, or reading about the relational database
model and the database-design process.
The section on value-related terms showed you that there is a distinct
difference between data and information, and that understanding this
difference is crucial to understanding the database-design process. You
now know quite a bit about nulls and how they affect information you
retrieve from the database.
Structure-related terms were covered next, and you learned that the
core structures of every relational database are fields, records, and
tables. You now know that views are virtual tables that are used, in
part, to work with data from two or more tables simultaneously. We
then looked at key fields, which are used to identify records uniquely
within a table and to establish a relationship between a pair of tables.
Finally, you learned the difference between a key field and an index.
Now you know that an index is strictly a software device used to opti-
mize data processing.
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Review Questions 73
In the section on relationship-related terms, you learned that a connec-
tion between a pair of tables is known as a relationship. A relationship
is used to help ensure various aspects of data integrity, and it is the
mechanism used by a view to draw data from multiple tables. You then
learned about the three characteristics of table relationships: the type
of relationship (one-to-one, one-to-many, many-to-many), the type of
participation (optional or mandatory), and the degree of participation
(minimum/maximum number of related records).
The chapter ended with a discussion of integrity-related terms. Here
you learned that a field specification establishes the general, physical,
and logical characteristics of a field—characteristics that are an inte-
gral part of every field in the database. You then learned that data
integrity is one of the most important aspects of the database-design
process because of its positive effect on the data in the database. Also,
you now know that there are four types of data integrity—three based
on database structure and one based on the way the organization
interprets and uses its data. These levels of integrity ensure the qual-
ity of your database’s design and the accuracy of the information you
retrieve from it.
Review Questions
1. Why is terminology important?
2. Name the four categories of terms.
3. What is the difference between data and information?
4. What does a null represent?
5. What is a null’s major disadvantage?
6. What are the chief structures in the database?
7. Name the three types of tables.
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74 Chapter 3 Terminology
8. What is a view?
9. State the difference between a key and an index.
10. What are the three types of relationships that can exist between a
pair of tables?
11. What are the three ways in which you can characterize a
relationship?
12. What is a field specification?
13. What three types of elements does a field specification
incorporate?
14. What is data integrity?
15. Name the four types of data integrity.
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Part II The Design Process
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77
4 Conceptual Overview
I don’t pretend to understand the Universe—it’s a great deal bigger than I am.
—THOMAS CARLYLE
Topics Covered in This Chapter
The Importance of Completing the Design Process
Defining a Mission Statement and Mission Objectives
Analyzing the Current Database
Creating the Data Structures
Determining and Establishing Table Relationships
Determining and Defining Business Rules
Determining and Defining Views
Reviewing Data Integrity
Summary
Review Questions
Understanding how to design a relational database isn’t quite as hard
as understanding the universe; in fact, it’s much easier. It is important
for you, however, to have an overall idea of the way the database-design
process works and a general idea of the steps involved within the pro-
cess. The purpose of this chapter is to provide an overview of the
database-design process.
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78 Chapter 4 Conceptual Overview
For the purpose of this overview, I’ve consolidated all of the techniques
in the design process into seven phases, and I discuss each phase in
general terms. This discussion provides a good overall picture of the
database-design process, and I hope it will give you a much clearer
understanding of each of the design techniques covered in Chapters 5
through 13.
You can use the design methodology in this book to design a new data-
base completely from scratch, refine an existing database, or help you
analyze an existing database so that you can design a new database
based on the results of your analysis.
The Importance of Completing the Design Process
One thing I want to make perfectly clear from the very beginning is the
importance of completing the design process. I’m often asked if it’s
truly necessary to go through the entire design process. My answer is
always a resounding yes! I’m then asked whether it’s still necessary if
someone is only going to create a “simple” database. (“Simple” is one of
the most dangerous words known to database developers. Nothing is
ever “simple.”) Again, my answer is yes, it’s still necessary. The type,
size, or purpose of the database is totally irrelevant to the value of
undertaking a fully developed design. You should implement and fol-
low the database-design process from beginning to end.
❖ Note A database can be designed by a single individual or a design team composed of two or more individuals. Throughout
the remainder of the book, I use the phrase “database developer”
and the word “developer” to refer to the person designing the
database.
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Defining a Mission Statement and Mission Objectives 79
It is a well-known and proven fact that it is a bad idea to attempt to
design a database without undertaking a complete database-design
process. Many database problems are caused by poor database design,
and partially following the design process is just about as bad as not
using it at all. An incomplete design is a poor design. Only following
through with a whole, unabbreviated design process assures a sound
structure and data integrity
An important point to keep in mind is that the level of structural integ-
rity and data integrity in your database is directly proportional to how
thoroughly you follow the design process. The less time you spend on the
design process, the greater the risk you run of encountering problems
with the database. Although thoroughly following the database-design
process may not eliminate all of the problems you may encounter when
designing a database, it will greatly help to minimize them. As you work
with your RDBMS software, you’ll find that a well-designed database is
easier to implement than a poorly designed one.
Databases are not hard to design; it just takes a little time to design
them properly. When it seems as if the design process is taking too
long, don’t allow yourself to take shortcuts—just be patient and
remember what a wise old sage once said:
There’s never time to do it right, but there’s always time to do
it over!
Defining a Mission Statement and Mission Objectives
The first phase in the database-design process involves defining a mis-
sion statement and mission objectives for the database. The mission
statement establishes the purpose of the database and provides you
with a distinct focus for your design work.
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Every database is created for a specific purpose, whether it’s to solve a
specific business problem, to manage the daily transactions of a busi-
ness or organization, or to be used as part of an information system.
You identify the purpose of your database and define it within a mis-
sion statement. This will help ensure that you develop an appropriate
database structure and that you collect the data necessary to support
the intended purpose of the database.
Along with the mission statement, you’ll define mission objectives in
this phase. Mission objectives are statements that represent the gen-
eral tasks your users can perform against the data in the database.
You use these objectives to support your mission statement and to help
you determine various aspects of the database structure.
There are two separate groups of people who will be involved in defin-
ing the mission statement and the mission objectives. The first group,
which includes the database developer (you), the owner or head of the
organization, and management personnel, is responsible for defining
the mission statement. The second group, which includes the data-
base developer (you again), management personnel, and end users, will
be responsible for defining the mission objectives.
Analyzing the Current Database
The second phase in the database-design process involves analyzing
the current database, if one exists. Depending on your organization,
the database will typically be a legacy database or a paper-based data-
base. A legacy database (also known as an inherited database) is one
that has been in existence and in use for several years or more. A
paper-based database, as you may already know, is a loose collection
of forms, index cards, manila folders, and the like. Whatever the data-
base type or condition, analyzing it will yield valuable information
about the way your organization is currently using and managing its
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Analyzing the Current Database 81
data. In addition, the analysis involves reviewing the way your organi-
zation is currently collecting and presenting the data. As the database
developer, you look at how your organization uses paper to collect data
(via forms) and present data (via reports). If your organization uses
some software application program to manage and manipulate the data
in the database, you study the way it collects and presents the data on-
screen. Finally, you take into account how (if at all) your organization is
using its data on the Web, and you review any browser-based applica-
tions that work with the database.
Another part of the analysis involves conducting interviews with users
and management to identify how they interact with the database on a
daily basis. As the database developer, you ask users how they work
with the database and what their information requirements are at the
current time. You then interview management personnel and ask them
about the information they currently receive and about their percep-
tion of the overall information requirements for the organization. These
interviews are an important component of your analysis because the
questions you ask (or don’t ask) will have a great impact on your final
database structure. You must conduct full and complete interviews if
you are to design a database that truly meets your organization’s infor-
mation needs.
Next, you use the information you’ve gathered from the analysis and
the interviews to compile an initial list of fields. You then refine this list
by removing all calculated fields and placing them on their own list;
you’ll use these calculated fields later in the design process. The
refined list constitutes your organization’s fundamental data require-
ments and provides a starting point for the design of a new database.
(As you know, nothing is ever truly final. Rest assured that you’ll
extend and refine this field list further as you develop your design.)
Once your initial field list is complete, you send it to your users and
management for a brief review and possible refinement. You encourage
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82 Chapter 4 Conceptual Overview
feedback and take their suggestions for modifications into consider-
ation. If you think the suggestions are reasonable and well supported,
you make the appropriate modifications, record the list in its current
state, and move on to the next phase.
Creating the Data Structures
Creating the data structures for the database is the third phase in the
database-design process. You define tables and fields, establish keys,
and define field specifications for every field.
Tables are the first structures you define in the database. You deter-
mine the various subjects that the tables will represent from the mis-
sion objectives you wrote during the first phase of the design process
and the data requirements you gathered during the second phase.
Then you establish these subjects as tables and associate them with
fields from the field list you compiled during the second phase of the
design process. After you’ve completed this task, you review each table
to ensure that it represents only one subject and that it does not con-
tain duplicate fields.
Now you go on to review the fields within each table. You refine all mul-
tipart or multivalued fields in the table so that they each store only a
single value, and you move or delete fields that do not represent dis-
tinct characteristics of the subject the table represents. When you
complete this review, you then review and refine the table structures.
This involves checking the work you performed on the fields to ensure
that you didn’t accidentally miss anything, and ensuring that each
table structure is properly defined. Next, you establish the appropriate
keys for each table. Your main task is to ensure that each table has a
properly defined primary key; this particular key uniquely identifies
each record within a table.
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Determining and Establishing Table Relationships 83
The final step in this phase is to establish field specifications for each
field in the database. Here you conduct interviews with users and man-
agement to help you identify the specific field characteristics that are
important to them and review and discuss any characteristics with
which they may be unfamiliar. After you’ve completed these interviews,
you define and document field specifications for each field. You then
review the table structures and field specifications with users and
management once more for possible refinements. The table structures
are ready for the next phase once you complete the refinements (if any)
that you identified during the review.
Determining and Establishing Table Relationships
The fourth phase of the database-design process involves establishing
table relationships. You conduct interviews with users and manage-
ment once again, identify relationships, identify relationship character-
istics, and establish relationship-level integrity.
Working with users and management is a prudent exercise because
they can assist you in identifying relationships among the data. You
cannot possibly be familiar with every aspect of the data your organiza-
tion uses, so leveraging whatever knowledge they have about the data
they use will be very beneficial to you.
After you’ve identified the relationships, you establish a logical connec-
tion between the tables in each relationship with a primary key or with
a linking table. What you actually use depends upon the type of rela-
tionship you’re establishing between the tables. Next, you determine
the type of participation and degree of participation for the tables in
each relationship. In some cases, these participation characteristics
will be obvious to you due to the nature of the data stored in the tables.
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In other cases, you’ll base the participation characteristics on specific
business rules.
Determining and Defining Business Rules
Determining and defining business rules is the fifth phase of the data-
base-design process. During this phase, you’ll hold interviews, identify
limitations on various aspects of the database, establish business
rules, and define and implement validation tables.
The manner in which your organization views and uses its data will
determine a set of limitations and requirements that you must build
into the database. Your interviews with users and management will
help you identify the specific constraints you will impose on the data,
data structures, or relationships. You then establish and document
these specifications as business rules.
The interviews you conduct with users will reveal specific limitations on
various aspects of the database. For example, a user working with an
order processing database is very aware of specific details, such as the
fact that a ship date must occur later than an order date; that there
must always be a daytime phone number; and that a shipping method
should always be indicated. On the other hand, your interviews with
management reveal general limitations on various aspects of the data-
base. The office manager for an entertainment agency, for example, is
familiar with general issues, such as the fact that an agent can repre-
sent no more than 20 entertainers and that promotional information
for each entertainer must be updated every year.
Next, you define and implement validation tables as necessary to sup-
port certain business rules. For example, if you find that certain fields
have a finite range of values because of the manner in which your orga-
nization uses them, you can use validation tables to ensure the consis-
tency and validity of the values stored in those fields.
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Reviewing Data Integrity 85
The level of integrity that business rules establish at this point is sig-
nificant because it relates directly to the way your organization views
and uses its data. As the organization grows, its perspective on the
data will change, which means that the business rules must change as
well. Determining and establishing business rules is an ongoing, itera-
tive process, and you must be constantly diligent if you are going to
maintain this level of integrity properly.
Determining and Defining Views
The sixth phase of the design process involves determining and defin-
ing views. Here you’ll conduct interviews (once again), identify various
ways of working with the data, and establish the views.
You identify the types of views you need to build in the database by
interviewing users and management and determining how they work
with their respective data. You may find, for example, that many users
require detailed information to perform their work, while others need
only summary information to help them make strategic decisions for
the organization. Each group of users must access information in very
specific ways, and you can use views to accommodate these situations.
Next, you define the views you’ve identified during the interview pro-
cess using the appropriate tables and fields, and establish criteria for
those views that are required to retrieve specific information. For
instance, you would establish criteria for a view that must list all cus-
tomers located in Texas or a view that must display the total number of
authorized vendors (by city) in Washington State.
Reviewing Data Integrity
The seventh and final phase in the database-design process involves
reviewing the final database structure for data integrity.
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First, you review each table to ensure that it meets the criteria of a
properly designed table, and you check the fields within each table for
proper structure. You then resolve any inconsistencies or problems you
encounter and review the structures once more. After you’ve made the
appropriate refinements, you check table-level integrity.
Second, you review and check the field specifications for each field. You
make necessary refinements to the fields and then check field-level
integrity. This review reaffirms the field-level integrity you identified
and established earlier in the database-design process.
Third, you review the validity of each relationship, confirm the relation-
ship type, and confirm the participation characteristics for each table
within the relationship. You then study relationship integrity to ensure
that there are matching values between shared fields and that there
are no problems inserting, updating, or deleting data in either of the
tables within the relationship.
Finally, you review the business rules that you identified earlier in the
database-design process and confirm the constraints you’ve placed on
various aspects of the database. If there are any other limitations that
have come to your attention since the last set of personnel interviews,
you establish them as new business rules and add them to the exist-
ing set of business rules.
You’re ready to implement your logical database structure in an RDBMS
program once you’ve completed the entire database-design process.
However, the process is never really complete because the database
structure will always need refinement as your organization evolves.
Summary
We began this chapter with a discussion of the importance of complet-
ing the design process, and you learned that designing a database
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Summary 87
without the benefit of a good design method leads to poor and improper
design. We also discussed the fact that the level of structural and data
integrity is in direct proportion to how thoroughly you follow the design
process. You then learned that inconsistent data and inaccurate infor-
mation are two problems typically associated with poorly designed
databases.
Next we looked at an overview of the entire database-design process.
The process was consolidated into the following phases in order to pro-
vide you with a clear picture of the general steps involved in designing
a database:
1. Define a mission statement and mission objectives for the data-
base. The mission statement defines the purpose of the database,
and the mission objectives define the tasks that are to be per-
formed by users against the data in the database.
2. Analyze the current database. You identify your organization’s
data requirements by reviewing the way your organization cur-
rently collects and presents its data and by conducting interviews
with users and management to determine how they use the data-
base on a daily basis.
3. Create the data structures. You establish tables by identifying the
subjects that the database will track. Next, you associate each
table with fields that represent distinct characteristics of the
table’s subject, and you designate a particular field (or group of
fields) as the primary key. You then establish field specifications
for every field in the table.
4. Determine and establish table relationships. You identify relation-
ships that exist between the tables in the database and establish
the logical connection for each relationship using primary keys
and foreign keys or by using linking tables. Then you set the
appropriate characteristics for each relationship.
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5. Determine and define business rules. You conduct interviews with
users and management to identify constraints that must be
imposed upon the data in the database. The manner in which
your organization views and uses its data typically determines the
types of constraints you must impose on the database. You then
declare these constraints as business rules, and they will serve to
establish various levels of data integrity.
6. Determine and establish views. You interview users and manage-
ment to identify the various ways they work with the data in the
database. When your interviews are complete, you establish views
as appropriate. You define each view using the appropriate tables
and fields, and you establish criteria for those views that must
display a limited or finite set of records.
7. Review data integrity. This phase involves four steps. First, you
review each table to ensure that it meets proper design criteria.
Second, you review and check all field specifications. Third, you
test the validity of each relationship. Fourth, you review and con-
firm the business rules.
Review Questions
1. Why is it important to complete the design process thoroughly?
2. True or False: The level of structural integrity is in direct propor-
tion to how thoroughly you follow the design process.
3. What is the purpose of a mission statement?
4. What are mission objectives?
5. What constitutes your organization’s fundamental data
requirements?
6. How do you determine the various subjects that the tables will
represent?
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Review Questions 89
7. True or False: You establish field specifications for each field in
the database during the second phase of the database-design
process.
8. How do you establish a logical connection between the tables in a
relationship?
9. What determines a set of limitations and requirements that you
must build into the database?
10. What is it that you can design and implement to support certain
business rules?
11. How do you determine the types of views you need to build in the
database?
12. When can you implement your logical structure in an RDBMS
program?
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5 Starting the Process
“Where shall I begin, please your Majesty?” he asked. “Begin at the beginning,” the King said gravely, “and go on till you come to the end: then stop.”
—LEWIS CARROLL ALICE’S ADVENTURES IN WONDERLAND
Topics Covered in This Chapter
Conducting Interviews
The Case Study: Mike’s Bikes
Defining the Mission Statement
Defining the Mission Objectives
Summary
Review Questions
Everything has a beginning, and the database-design process is no dif-
ferent. Interestingly enough, you start the process by defining the end
result. It is in the very first step of the database-design process that
you identify and declare the purpose of the database. You also define
and declare a list of the tasks that your users can perform against the
data in the database. Both of these items provide you with a focus and
direction for developing a database, and they help ensure that your
final database structure supports the stated purpose and tasks.
Conducting Interviews
Interviews are an integral part of database design, and they play a key
role during certain phases of the design process. Assuming that you
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work within some organization and need to design a database to sup-
port the work that you and your fellow employees perform, you should
make certain that you conduct your interviews in the manner
described in this book. This means that throughout the design pro-
cess, you’ll interact with some of your fellow employees, management
personnel, and (depending on the size of the organization) the owner. If
you work for a small organization that employs only a handful of peo-
ple, or if you are only creating a database for yourself, you’ll conduct
“self-interviews”; you’ll still conduct the interviews described in this
book, but you will act as the interviewer and the interviewee. You will
be the one who provides the answers to the questions.
Interviews are important because they provide a valuable communica-
tion link between you (the developer) and the people for whom you’re
designing the database, help ensure the success of your design efforts,
and provide critical information that can affect the design of the data-
base structure. As you’re working with table relationships, for example,
you might find it difficult to determine the type of participation and
degree of participation for a specific relationship. The only way for you
to determine the proper values for these relationship characteristics is
to conduct an interview with the appropriate people in your organiza-
tion. You can then use the information you gathered during the
❖ Note Interviewing is a skill that you can learn with some amount of patience, diligence, and practice. There are a variety of
approaches and techniques you can use to conduct an inter-
view, and there are numerous academic papers, articles, and
books that have been written on the subject. Although an in-
depth discussion of this topic is beyond the scope of this book,
I’ve included several techniques and guidelines in this chapter
that will help you conduct your interviews efficiently and
effectively.
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Conducting Interviews 93
interview to set the relationship characteristics. Using an interview as
an information-gathering tool, you can gain new insights from partici-
pants regarding part of the database or clarify facts that you don’t
understand. Note that you must always conduct each of the interviews
incorporated within this design process, regardless of the type of data-
base you’re designing or the number of people involved. You will
inevitably miss some piece of important information when you neglect
or omit any of the interviews, and this could adversely affect the final
structure of your database.
Always establish guidelines for your interviews before you conduct
them. This will help ensure that you conduct your interviews in a con-
sistent manner and that they are always (or usually) successful. Here
are some guidelines you can establish for the participants and for
yourself.
Participant Guidelines
• Make the participants aware of your intentions. Many people are
wary of interviews. They don’t like to be “put on the spot” and
they don’t want to be asked “trick” questions. Let each person
know the subject you wish to discuss, the names of the other par-
ticipants, the time you want to start the session, and whether this
interview is part of an ongoing series of interviews. If everyone
participating in a given interview session knows how you’re going
to conduct it and what you expect of them, they’re more likely to
engage in the conversation at hand and be quite responsive to
❖ Note Throughout the remaining chapters, I use open-ended questions for all interviews that are part of the concept or tech-
nique under discussion. You can use these questions as a guide
for formulating your own questions for a given interview.
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your questions. Above all, reassure them that the interview is not
a disguised assessment of their performance; you want to make
certain they feel comfortable talking to you openly and without
reservation. This will go a long way toward building a foundation
of trust between you and the participants.
• Let the participants know that you appreciate their taking part in
the interview and that their responses to the interview questions
are valuable to the overall design project. Earlier experiences are
likely to make some people believe that whatever input they pro-
vide goes unnoticed and unappreciated at work. Even when in
the past their input made a significant impact on a specific
project, rarely did they get so much as a thank-you. In light of
this, there’s no real motivation for them to participate in your
interview. Many, if not all, of your participants will start out with
this attitude. But you can really increase their motivation by let-
ting them know that you truly and honestly appreciate their
participation and are very interested in their responses. Assure
them that their feedback is truly valuable to the design process
and that in many cases their responses can substantiate and val-
idate decisions made throughout the design process. If you make
yourself credible by being genuinely sincere, participants will
help you in any way they can. Your job will be much easier and
everyone will participate voluntarily and enthusiastically. It’s very
effective to show, on a second interview, how you have already
used participants’ earlier contributions.
• Make sure everyone understands that you are the official arbitra-
tor if and when a dispute arises. It’s inevitable that minor disputes
will arise during an interview and that there will be some amount
of tension until such disputes are resolved. You can avoid this sit-
uation by arbitrating these disputes yourself. As the database
developer, you’re in the best position to do this because you have
an objective viewpoint and can see both sides of an issue. Addi-
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Conducting Interviews 95
tionally, the decision you make will always be in the best interests
of the database structure. Always remember that disputes deal-
ing with something other than the database structure can be
referred to a more appropriate authority, if one exists.
Interviewer Guidelines (These Are for You)
• Conduct the interview in a well-lit room, separated from distract-
ing noise, with a large table and comfortable chairs, and have
coffee and munchies on hand. You’ll greatly enhance your
chances of carrying out a successful interview when you pay
attention to atmosphere. Use a well-lit room because it allows the
participants to read your interview materials very easily. A large
table ensures that everyone has space to work, and comfortable
chairs keeps them relaxed enough to concentrate on the conver-
sation at hand. Always have plenty of coffee available, as this
seems to be the preferred beverage of businesspeople every-
where. Finally, provide a good supply of munchies to help keep
everyone in a good mood. People actually seem to think better
when they have something to munch on—it keeps their mouths
occupied while they’re thinking. (The business climate has
changed considerably since I first wrote this book. Many people
are now conducting interviews and meetings in restaurants or at
the local Starbucks. You might consider this as an option if you
can’t devise an appropriate setting for your interviews.)
• Set a limit of 10 people for each interview. Limiting the number of
participants promotes a more relaxed atmosphere and makes it
easier for you to encourage everyone to participate. One problem
you’ll find in conducting an interview with a large number of peo-
ple is that the intimidation level of some of the participants will
rise in direct proportion to the number of participants taking part
in the interview as a whole. Some people are just afraid of looking
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ignorant or incompetent in front of their colleagues, whether or
not there’s truly any justification for such feelings. So, you do
have a very good reason to restrict the number of participants in
an interview.
• Conduct separate interviews for users and management. Separat-
ing the two groups is a good idea for a variety of reasons, including
the “fear factor” noted above. Primarily, you want to separate them
because each group has a different perspective on the organiza-
tion as a whole and how the organization uses its data on a daily
basis. Conducting separate interviews for each group allows you to
leverage their unique perspectives to your advantage as you work
through the database-design process. Another reason for keeping
the interviews separate is to eliminate the conflicts that can arise
when these groups disagree over certain aspects of the organiza-
tion. It’s quite common for there to be a lack of communication
between them, and the odds are 50/50 that the interview will
bring this problem to the surface. This may impel them to estab-
lish better lines of communication, or it may exacerbate the
problem further. In any case, this communication problem can
complicate and extend your interview and diffuse its results. Use
your knowledge of the organization to help you judge whether to
keep the interviews separate. If you need to conduct an interview
with both groups at the same time, do so intentionally, with a spe-
cific purpose in mind, and be prepared for distractions.
• When you have to interview several groups of people, designate a
group leader for each group. The group leader will help you
ensure that the interview runs smoothly. She will be responsible
for preparing each member of her group for the interview and for
providing you with any new information she obtained from the
group outside of the interview. During the interview, the group
leader can direct your questions to the member best equipped to
answer them.
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You’ll occasionally encounter a group leader who may want to
dominate the interview and answer every one of your questions.
When this happens, diplomatically and politely inform him that it
is your job (and duty) to obtain feedback from all of the partici-
pants, so that you can make a complete assessment of the
organization’s overall information requirements. If this doesn’t
rectify the problem, you have the option of designating someone
else as the group leader or refraining from including him in
future interviews.
• Prepare your questions prior to the interview. You can conduct an
interview rather easily if you have a set of prepared questions.
(Coming up with questions off the top of your head is rarely a
good idea, even if you’re an experienced interviewer and are
highly skilled at producing ad hoc questions.) Having a prepared
list of questions allows you to provide a focus and direction for
the interview, and it provides the participant with a continuity of
thought. Your interview will flow more smoothly and will be more
productive when your questions move easily from topic to topic.
As you prepare your list of interview questions, make sure you
use open-ended questions. For example, “Did you feel our service
was (a) poor, (b) average, or (c) good” is a closed question. A
closed question isn’t particularly useful because it supplies its
own set of responses and does not allow an interviewee to pro-
vide an objective opinion or elaborate answer. On the other hand,
an open-ended question, such as “How do you feel about our ser-
vice?” is far more useful because it allows the interviewee to
answer the question in a variety of ways. There are times when
you may need to use closed questions, but it’s better to use them
intentionally, sparingly, and with a specific purpose in mind.
• If you’re not very good at taking notes, either assign that task to
a dependable transcriber for each interview or get the group’s
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permission to use a tape recorder to record the interview. You
conduct interviews to gather specific information about the
organization, so it’s important that you establish a detailed
record of each interview. If you find it difficult to conduct an
interview and take notes at the same time, you should enlist
one of the participants as your assistant and have him take
notes for you. (This is one good way to encourage participation
from people who are normally quiet or reserved.) Choose your
assistant carefully because the notes may suffer if he is at all
distracted by the proceedings. Another option you have avail-
able is to use a tape recorder to record the interview. This might
prove to be a better way to handle your notes because the tape
recorder will capture the interview more accurately, and you’ll
be able to determine exactly who provided you with a given
piece of information. (If you do decide to record the interview, be
sure you first obtain permission from each of the participants.
There may be privacy or confidentiality issues at stake, and you
don’t want to get yourself into any kind of trouble.)
• Give everyone your equal and undivided attention. This is a cru-
cial point for you to remember: You must pay complete attention
to the person who is speaking, and do so sincerely. If you give a
participant the impression that you’re bored, uninterested, or
preoccupied, he will immediately reduce his level of participation
within the interview. On the other hand, he will probably partici-
pate quite enthusiastically if he sees that you are interested in
what he’s saying and has your undivided attention.
There will be times when a participant responds to your ques-
tions with vague or incomplete answers. He may respond this
way for several reasons. It may be that he doesn’t quite know
how to express the ideas he wants to convey or that he’s not at
liberty to divulge certain information. It could also be that he’s
just not comfortable talking about himself and what he does or
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that he is suspicious of you for some reason. In any case, you’ll
have to be patient and make him feel at ease so that he will pro-
vide you with the information you need. For example, you could
try to state your best approximation of what he’s said thus far
and ask if it is what he meant to say.
• Keep the pace of the interview moving. You’ve probably attended
meetings during which a particular point was belabored or much
time was spent trying to extract information from a reluctant
participant. You can prevent this from happening during your
interviews by setting personal limits on the time you’ll allow for a
question to be answered and the time you’ll spend on a specific
topic. Don’t inform the participants about this limit; instead, try
to promote a sense of urgency.
• Always maintain control of the interview. This is the single most
important guideline for every interview you conduct. Inevitably,
something goes wrong the moment you lose control of the inter-
view. For instance, say you have a situation where one of the
participants begins to change the focus of the interview by dis-
cussing issues that have little or no relevance to the topics on
your agenda. You’ll certainly lose control of the interview unless
you do something to redirect the discussion. Regaining control of
the interview will be easy for you to do in some cases, but in oth-
ers you’ll just have to declare your portion of the interview
“complete” and let the participants carry on with their discus-
sion. You can avoid situations like this so long as you maintain
control of the interview.
Interviews are an integral part of the design process, and I provide
examples of them throughout the next several chapters. You’ll find
sample dialog that illustrates typical interview scenarios and examples
of questions you might use during a given interview. (The sample ques-
tions always relate to the type of interview you’re currently conducting.)
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One final point: Keep in mind that the guidelines I’ve presented in this
section are merely recommendations. I suspect that you won’t be able
to apply all of these guidelines to every interview you conduct. How-
ever, I would expect you to apply them in an ideal situation. Yes, I
know—you don’t come across ideal situations all the time. Neither do I.
But you can still make it your goal to meet as many of these guidelines
as possible. In the end, the person who stands to gain the most is you.
The Case Study: Mike’s Bikes
There are numerous examples throughout the book that illustrate the
concepts and techniques used in the database-design process. I’ve
drawn these examples from a variety of databases and used them in an
arbitrary fashion. Using them in this manner allows me to demon-
strate that once you learn how to apply a particular concept or
technique generically, you can then apply it to any other database
you’re designing. Therefore, your focus should always be on the con-
cept or technique being presented, not on the example itself.
Nevertheless, I use a single database example as a case study to illus-
trate the steps involved in the design process. This enables me to
present the process with some degree of continuity. As the database-
design process unfolds, I apply each technique to designing the data-
base for the fictitious company in the case study. I provide only a few
details about the company in this chapter, but I’ll supply more as I
present each new concept or technique.
❖ Note The purpose of an interview example is to illustrate the techniques you use to conduct a specific type of interview, and
I’ve kept the dialog relatively simple for this reason. However, the
dialog will still provide you with good ideas for the types of con-
versations you conduct in the interview.
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Defining the Mission Statement 101
Mike’s Bikes, our case-study business, is a new bike shop located in a
small suburb called Greenlake, not far from downtown Seattle. It has
been open for only two months, and business is growing steadily. Mike,
the shop’s owner, has been conducting his daily business on paper. He
records sales on preprinted forms, maintains employee and vendor
information on sheets of paper (storing them in manila folders), and
writes information about his regular customers on index cards. As a
result, Mike spends a lot of time maintaining all of this data. He owns a
computer but uses it mainly to play games, write letters, and visit vari-
ous golf sites. The only business-related task he performs on the
computer is keeping track of the bike shop’s inventory using a spread-
sheet program.
Recently, Mike learned that using a database would be a good way to
store and work with data related to his business. Using a database
would greatly diminish the amount of time he currently spends main-
taining his data, and he could always ensure that the data is up-to-date
and that the information is accurate. Although he thinks a database is
a good idea, he’s aware of the fact that he doesn’t know the first thing
about properly designing a database. Undaunted, Mike has decided to
hire a database consultant to design the database for him.
You are, in this fable, the consultant he has hired for the project. As
the database-design process unfolds throughout the next several chap-
ters, you’ll apply each technique to design the database for Mike’s
Bikes. As you learn new concepts or techniques, Mike will supply you
with the information you need to complete the design of his database.
Defining the Mission Statement
In the previous chapter, you learned that the mission statement declares
the specific purpose of the database in general terms and that you
define it at the beginning of the database-design process. Furthermore,
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it provides you with a focus for your design efforts and keeps you from
getting diverted and making the database structure unnecessarily large
or complex.
The Well-Written Mission Statement
A good mission statement is succinct and to the point. Verbose state-
ments have a tendency to be confusing, ambiguous, or vague; they do
more to obscure the purpose of the database than to clarify it. Here is
an example of a typical mission statement:
The purpose of the New Starz Talent Agency database is to
maintain the data we generate, and to supply information that
supports the engagement services we provide to our clients and
the management services we provide to our entertainers.
This mission statement is well-defined and uncluttered by unneces-
sary statements or details. It is a very general statement, just as it
should be. Think of a mission statement as the flame of a candle lo-
cated at the end of a dark tunnel. The light produced by the flame
guides you to the end of the tunnel, so long as you focus on it. In the
same manner, the mission statement guides you to the end of the data-
base-design process. Guided by your mission statement, you can focus
on designing a database structure that will support the declared pur-
pose of the database.
A well-written mission statement is free of phrases or sentences that
explicitly describe specific tasks. If your mission statement contains
these types of phrases or sentences, remove them and rewrite the
statement. Be sure to keep the discarded phrases handy, though,
because you may be able to use them to formulate mission objectives.
(You’ll learn about mission objectives in the next section.) Here’s an
example of a poorly worded mission statement:
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Defining the Mission Statement 103
The purpose of the Whatcom County Hearing Examiner’s data-
base is to keep track of applications for land use, maintain data
on applicants, keep a record of all hearings, keep a record of all
decisions, keep a record of all appeals, maintain data on depart-
ment employees, and maintain data for general office use.
It should be immediately apparent that there are a few things wrong
with this mission statement.
• It’s slightly verbose. Remember that the ideal mission statement
should be succinct and to the point.
• The specific purpose of the database is unclear. This mission
statement is written in such a way that it is difficult for you to
ascertain the specific purpose of the database.
• It describes several specific tasks. Two issues arise when a mis-
sion statement is written in this manner. First, the description of
the tasks does nothing to define the specific purpose of the data-
base. Second, the statement somehow appears to be incomplete.
It raises the question “Are there any tasks we’ve forgotten to
include in the mission statement?”
You can fix this mission statement by removing the references to spe-
cific tasks (be sure to save them for the next step) and rewriting the
statement. Here is an example of one of the possible ways you could
rewrite this mission statement:
The purpose of the Whatcom County Hearing Examiner’s data-
base is to maintain the data the examiner’s office uses to make
decisions on land-use requests submitted by citizens of What-
com County.
Notice how the purpose of the database has become much clearer in
this version. Also note that the statement is more succinct and doesn’t
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give the impression of being incomplete. You’ll always have a clear
focus during the database-design process when you formulate your
mission statements in this manner.
Composing a Mission Statement
The process of creating a mission statement involves conducting an
interview with the owner or manager of the organization, learning
about the organization, and determining the purpose of the new
database.
You conduct the interview for this step with the owner of the organiza-
tion or, if he directs, the appropriate staff. Either will be able to help
you define the statement because each has an overall understanding of
the organization and a general comprehension of why the database is
necessary in the first place. Besides helping you to define the mission
statement, this interview will also provide a great deal of information
about the organization itself. This information is valuable because you
can use it later in the design process.
As you conduct the interview, encourage the interview participant to
discuss as many facets of the organization as she can, even if the dis-
cussion relates to issues that aren’t directly relevant to the database.
The idea here is for you to understand what the organization does and
how it functions; the more you understand an organization, the better
prepared you will be to design a database that will fulfill its needs. The
organization’s general need for a database will become clear to you
once you have a better understanding of the organization itself. You
can then translate this need into a mission statement.
Be sure to ask open-ended questions during the interview. In some
cases, a good question can prompt the participant to state the purpose
of the database without much effort. For example, say you posed the
following question:
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“How would you describe the purpose of your organization to a
new client?”
This is a good open-ended question because it focuses on the issue
yet gives the participant the freedom to respond with what she feels is
a complete answer. Furthermore, this type of question will typically
generate a response that you can translate directly into a mission
statement.
Now assume you received the following reply:
“We supply entertainment services to our clientele for any and
all occasions. We take care of all the details for the engagement
so that it is as worry-free for the client as possible.”
You can easily rewrite this type of response and turn it into a mission
statement. In fact, when a response such as this one consists of two or
more sentences or phrases, one of the sentences or phrases typically
indicates the purpose of the database. For example, you can use the
first sentence from the reply above to construct the mission statement.
Here is one of several ways you could rewrite the reply:
The purpose of the All-Star Talent database is to maintain the
data we use in support of the entertainment services we pro-
vide to our clientele.
The most important point to remember is that the mission statement
should make sense to you (the database developer) and to those for
whom you are designing the database. Different groups of people have
different ways of phrasing statements, and the specific wording of the
statement can depend greatly on industry-specific terminology. Your
mission statement is complete when you have a sentence that
describes the specific purpose of the database and that is understood
and agreed upon by everyone concerned.
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Here are a few sample questions that you can use to arrive at your mis-
sion statement:
How would you describe the purpose of your organization to a
new client?
What would you say is the purpose of your organization?
What is the major function of your organization?
How would you describe what your organization does?
How would you define the single most important reason for the
existence of your organization?
What is the main focus of your organization?
You may have noticed that some of these questions seem to be the
same question rewritten in a different manner. Keep in mind that the
observation regarding the phrasing of mission statements also applies
to the interview questions you’ll use throughout the database-design
process. You can pose the same question to several people and receive
different responses because each person may interpret the meaning of
the question a little differently. In some cases, you may just get a long,
“I haven’t had my first espresso yet” type of stare. Experiment with dif-
ferent types of phrasing and determine which type works best for you.
Your method of constructing and posing questions may be different
from someone else’s, but it doesn’t matter as long as you have a
method that suits you.
Now you need to define a mission statement for Mike’s Bikes. Before
you can define the mission statement, you must conduct an interview
with the owner to gather information about his business. Assume you
CASE STUDY
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have an assistant named Zachary who is conducting the interview for
you. The interview may go something like this:
ZACHARY: “Can you tell me why you believe you need a database?”
MIKE: “I think we need a database just to keep track of all our
inventory. I’d also like to keep track of all our sales as
well.”
ZACHARY: “I’m sure the database will address those issues. Now,
what would you say is the single most important func-
tion of your business?”
MIKE: “To provide a wide array of bicycle products and bicycle-
related services to our customers. We have a lot of great
customers. And regular ones, too! They’re our biggest
asset.”
(The interview continues until Zachary has finished asking all the
questions on his list.)
After the interview, review the information you’ve gathered and define
the mission statement. You can ascertain a few points from the previ-
ous dialog with Mike, such as the fact that he’ll need to be able to track
products, customers, and customer sales. But the most valuable point
is provided by his reply to the second question. You can use the first
sentence in that reply to formulate the mission statement. Taking into
account some of the other points you’ve identified in the interview, you
can rewrite Mike’s reply to create the following mission statement:
The purpose of the Mike’s Bikes database is to maintain the
data we need to support our retail sales business and our
customer-service operations.
When you feel you have a good mission statement, review it with Mike
and make sure that he understands and agrees with the declared pur-
pose of the database. When you and Mike are satisfied with the mission
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statement, you can go on to the next step, which is defining the mis-
sion objectives.
Defining the Mission Objectives
To expand upon the overview in the previous chapter, mission objec-
tives are statements that represent the general tasks supported by the
data maintained in the database. Each mission objective represents a
single task. These mission objectives provide information that you’ll
use throughout the database-design process. For example, mission
objectives help you define table structures, field specifications, relation-
ship characteristics, and views. They also help you establish data
integrity and define business rules. Finally, mission objectives guide
your development efforts and ensure that your final database struc-
ture supports the mission statement.
Well-Written Mission Objectives
A well-written mission objective is a declarative sentence that clearly
defines a general task and is free from unnecessary details. It is
expressed in general terms, succinct and to the point, and unambigu-
ous. Here are some examples of typical mission objectives:
We need to maintain complete patient address information.
We need to keep track of all customer sales.
We need to make sure an account representative is responsible
for no more than 20 accounts at any given time.
We need to keep track of vehicle maintenance.
We need to produce employee phone directories.
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Defining the Mission Objectives 109
These mission objectives are well defined and easy to understand. Each
mission objective represents a single general task and defines the task
clearly without unnecessary details. For example, the last mission
objective in the list states that employee directories need to be pro-
duced, but it doesn’t indicate how they are to be produced. It is not
necessary to indicate how the employee lists will be produced because
that issue is part of the application-development process. Remember
that the purpose of a mission objective is to help define various struc-
tures within the database and to help guide the overall direction of the
database’s development.
If a mission objective represents more than one general task, you
should decompose it into two or more mission objectives. Here is an
example of a poorly written mission objective:
We need to keep track of the entertainers we represent and the
type of entertainment they provide, as well as the engagements
that we book for them.
There are two problems with this mission objective:
1. It defines more than a single general task. It is clear that there are
two tasks represented in this statement: keeping track of enter-
tainers and keeping track of engagements.
2. It contains unnecessary detail. It’s unnecessary to refer to the
entertainer’s “type of entertainment” in this mission objective. The
phrase “type of entertainment” either refers to a distinct charac-
teristic of an entertainer, or it represents a new task that should
be declared as a mission objective. If it refers to a distinct charac-
teristic of an entertainer, it should be removed from the
statement; otherwise, it should be used as the basis for a new
mission objective.
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You can fix this mission objective by removing the unnecessary detail
and rewriting it as two mission objectives. (Keep the details you dis-
card on a separate piece of paper; they may be useful later in the
design process.) Here is an example of one possible revision:
We need to maintain complete entertainer information.
We need to keep track of all the engagements we book.
Notice that each mission objective now clearly defines a single general
task and is easy to understand as well. Mission objectives such as
these are easy to use as you design the database.
Composing Mission Objectives
Defining mission objectives is a process that involves conducting inter-
views with users and management and then writing appropriate
mission objectives based on the information gathered from the
interviews.
The purpose of the interview is to determine what types of general tasks
need to be supported by the data in the database. You accomplish this
by asking the participants open-ended questions and allowing them to
elaborate on their replies as necessary. The mission statement and mis-
sion objectives interviews are the easiest ones you’ll conduct during the
design process because everyone is usually enthusiastic about partici-
pating. It’s fairly easy to get people to discuss what they do on a daily
basis and to give their perspective on the function of the organization.
This is also one of the few interviews you’ll conduct with both users and
management; there should be a lot of common ground between the two
groups due to the general nature of the interview.
One very important point to remember is that the interviews you con-
duct here involve very general discussions. The discussions are more
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Defining the Mission Objectives 111
conceptual than analytical; your intent here is not to analyze the cur-
rent database or database application, but to get an overall idea of the
general tasks the database should support. Keep in mind that one of
the purposes of the mission objectives is to help guide the develop-
ment of the database structure.
As you conduct the interview, be sure, once again, to ask open-ended
questions. Remember that open-ended questions are apt to elicit bet-
ter responses from your participants. Ask the participants questions
regarding their daily work, how the organization functions, and what
type of issues they believe need to be addressed by the database.
Encourage them to discuss as many facets of their work and the orga-
nization as they possibly can. As they reply, try to record each
response as a declarative sentence. You’ll find it is much easier to
transform a sentence into a mission objective if you can do this. Here
are just a few examples of the types of questions you could pose dur-
ing the interview:
What kind of work do you perform on a daily basis?
How would you define your job description?
What kind of data do you work with?
What types of reports do you generate?
What types of things do you keep track of?
What types of services does your organization provide?
How would you describe the type of work you do?
All of these questions are likely to evoke a good, lengthy response from
the participant. One of the advantages of questions like these is that
they provide the opportunity for you to ask follow-up questions. For
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example, say you received the following response to the last question in
the list:
“First, I try to determine the general problem with the vehicle.
Then I fill out a work order and note my assessment of the
problem. Finally, I send the vehicle to the next available service
team.”
You’ll immediately notice that it’s a lengthy response, which is fine. You
should also note that you could easily ask a follow-up question, such
as the following:
“Is there any type of customer information incorporated within
the procedure you just described?”
Even if the reply is no, the question is still open-ended enough for the
participant to elaborate further on his original response. This type of
follow-up question could also jar his memory and cause him to relay
other information, which may be related to the subject of the original
response.
Here is a set of mission objectives that you could derive from the par-
ticipant’s original response:
We need to maintain information on customer vehicles.
We need to keep track of work orders.
We need to maintain information on our service teams.
We need to maintain information on our mechanics.
We need to maintain information on our customers.
Three of these objectives are derived directly from the response. They’re
easy for you to determine because their subjects are explicitly stated in
the response itself. The last two mission objectives are derived from
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Defining the Mission Objectives 113
assumptions based on the response. This is a technique (which you can
think of as “reading between the lines”) that experienced database
designers use quite often, and it is one that you should use when you’re
defining mission objectives. The technique relies on your ability to deter-
mine what information a response conveys implicitly, as well as what it
conveys explicitly. So pay attention. Listen for implications. Without good
assumptions, your overall set of mission objectives could be incomplete.
Review the following response and determine whether there is implicit
information hidden within the response itself:
“I book entertainment for our clientele, which consists of com-
mercial and noncommercial clients. Our noncommercial clients
are typically individuals or small groups who book weddings,
birthdays, anniversaries, and the like. Our commercial clients,
on the other hand, consist of businesses, such as nightclubs
and corporations. The nightclubs book entertainment in six-
week slots; the corporations book things, such as corporate par-
ties, product rollouts, and various types of promotional
functions.”
Aside from the explicit information that this response conveys, there
are at least two pieces of implicit information that you can uncover in
this response. The first piece of implicit information concerns the need
to maintain information on the entertainers booked for the engage-
ments. An agent needs to know things such as the entertainer’s name,
phone number, mailing address, availability, and whether he will travel
to out-of-town locations. The second piece of implicit information con-
cerns the need to maintain information on the engagements them-
selves. An agent must know all the details concerning the engagement
in order to ensure that the engagement runs smoothly.
Now that you know how important it is to look for implicit information,
keep it in mind when you’re defining mission objectives.
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Here are the “final words” regarding mission objectives: Make sure that
your mission objectives are both properly defined and well defined, that
each objective makes sense to you and to those for whom you are
designing the database, and that you look for any implicit information
hidden within every participant’s response.
It’s time now to interview Mike and his staff so that they can help you
define the mission objectives for the Mike’s Bikes database. Here’s a
partial transcript of the interview with Mike. Once again, your assis-
tant, Zachary, is conducting the interview.
ZACHARY: “Can you give me an idea of the things you’d like to track
in the database?”
MIKE: “Oh sure, that’s pretty easy. I want to keep track of our
inventory, our customers, and our sales.”
ZACHARY: “Is there anything else that you can think of that is
related to these subjects?”
MIKE “Well, I guess if we’re going to keep track of our inven-
tory, we should know who our suppliers are.”
ZACHARY: “What about the sales reps involved in each sale?”
MIKE: “Oh yeah, we should definitely keep information about
our employees. If nothing else, it’s a good idea to do this
from a human-resources point of view. At least, that’s
what my wife tells me!”
(The interview continues until Zachary has finished asking all the
questions on his list.)
When the interviews are complete, review all the information you’ve
gathered and define the appropriate mission objectives. Be sure to keep
the “final words” in mind as you define them. Here are a few possible
mission objectives for the Mike’s Bikes database.
CASE STUDY
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We need to maintain complete inventory information.
We need to maintain complete customer information.
We need to track all customer sales.
We need to maintain complete supplier information.
We need to maintain complete employee information.
Once you’ve compiled a list of mission objectives, review them with Mike
and his staff. When they are satisfied that they understand the mission
objectives and that the list is relatively complete, commit the list to a
document in your favorite word processor and save it for later use.
Summary
This chapter opened with a discussion of the interview process. You
learned why interviews are an important part of the database-design
process and why it’s important to learn how to conduct an interview
properly. You now know the difference between an open-ended question
and a closed question, as well as when to use each kind of question. We
ended this discussion by reviewing a set of interview guidelines, and
you learned that you should use them to help you ensure that the inter-
views are productive and successful.
The mission statement was our next topic of discussion. We expanded
upon the Chapter 4 overview by looking at how the mission statement
states the specific purpose of the database. You now know that the pro-
cess involves conducting interviews and learning about the organiza-
tion, then formulating the mission statement from the information you
gathered during these steps. We defined the characteristics of a good
mission statement, and you learned that a well-defined mission state-
ment establishes a clear focus for your design efforts.
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Next, we discussed mission objectives, and we expanded upon the
Chapter 4 overview once again. As you now know, mission objectives
represent the tasks performed against the data in the database, and
you define them after the mission statement. We then explored how to
define a mission objective. Here, you learned that you conduct inter-
views with users and management and that the information you gather
from these interviews provides the basis for each mission objective. We
also discussed the characteristics of a well-written mission objective,
and you learned that a clearly defined mission objective will help you
define various structures within the database.
Review Questions
1. Why are interviews important?
2. What problem can arise when you conduct an interview with a
large number of people?
3. What is the primary reason for conducting separate interviews
with users and management?
4. True or False: You’ll commonly use closed questions in your
interviews.
5. What kind of responses should you try to evoke from the inter-
view participants?
6. What is the single most important guideline for every interview
you conduct?
7. What is a mission statement?
8. State two characteristics of a well-written mission statement.
9. True or False: You need not learn about the organization in order
to compose a mission statement.
10. When is your mission statement complete?
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Review Questions 117
11. What is a mission objective?
12. State two characteristics of a well-written mission objective.
13. True or False: You should interview users and management to
help you define mission objectives.
14. How does the staff’s daily work relate to the mission objectives?
15. True or False: A mission objective can describe more than one
task.
16. State two ways that a mission objective can be derived from a
response.
17. When is a mission objective complete?
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119
6 Analyzing the
Current Database
To see what is in front of one’s nose needs a constant struggle.
—GEORGE ORWELL IN FRONT OF YOUR NOSE
Topics Covered in This Chapter
Getting to Know the Current Database
Conducting the Analysis
Looking at How Data Is Collected
Looking at How Information Is Presented
Conducting Interviews
Interviewing Users
Interviewing Management
Compiling a Complete List of Fields
Case Study
Summary
Review Questions
Getting to Know the Current Database
To determine where you should go, you must first understand
where you are.
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This maxim defines the entire philosophy behind this phase of the data-
base-design process. You must devote some time to gaining a clear un-
derstanding of your organization’s database for these reasons:
• To determine whether the database supports the organization’s
current information requirements
• Τo uncover existing structural deficiencies
• To determine how the database needs to evolve so that it will
support the organization’s future information requirements
You can use the existing database as a resource for developing a new
database. However, you must carefully judge which aspects of the cur-
rent database remain useful and which aspects should be discarded.
You can make these judgments by answering the following questions:
What types of data does the organization use?
How does the organization use that data?
How does the organization manage and maintain that data?
The answers to these questions provide you with vital information that
you can use to design a database that best suits your organization’s
needs.
You can best answer these questions by analyzing your organization’s
existing database. It’s very likely that the organization is using some
type of database, and it can probably be associated with one of the fol-
lowing categories:
• Paper-based databases—also known as file systems—typically
consist of various forms and handwritten documents stored in
file folders or bound in notebooks. The folders and notebooks are
identified by some coding scheme (e.g., unique numbers or col-
ored tabs) and stored in file cabinets. These cabinets are likely to
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Getting to Know the Current Database 121
be identified by some coding scheme as well, depending on the
size of the database.
• Legacy databases have been in existence and in use for several
years or more and consist of various types of data structures and
character-based user interface screens that all reside on a main-
frame computer or personal computer. The capability,
functionality, and effectiveness of the structures and screens are
quite dependent upon the programming language and database-
management software used to create them. In general, the struc-
tures and screens are crude by today’s standards because they
were created at a time when programming languages and data-
base software were not as sophisticated as those we’ve come to
know since the mid-1990s.
• Human-knowledge bases (loosely defined) are based on the mem-
ory of one or more employees within an organization. These
individuals have a specific amount of knowledge regarding a
given aspect of the organization (e.g., customer information or
product details), and they are crucial to conducting the organiza-
tion’s business.
The goal of your analysis is to determine the types of data the organiza-
tion uses, how the organization manages and maintains that data, and
how the organization views and uses the data. You can reduce the time
it takes to define the preliminary field and table structures for the new
database if you conduct this investigation properly.
During the analysis, you review the various ways the organization col-
lects and presents its data, and you conduct a set of interviews with us-
ers and management. You then use the information you’ve gathered to
define a preliminary field list and to help you determine the tables that
should be included in the initial database structure. If your analysis re-
veals that the current database is poorly designed, you can take precau-
tions to ensure that you don’t make the same mistakes in the new
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database. Despite whatever shortcomings the current database may
have, it can still help you identify a number of the fields and tables that
you should include in the new database.
There’s one rule you should keep first and foremost in your mind as
you’re analyzing the current database:
Do not adopt the current database structure as the basis for
the new database structure.
Following this rule will help you avert unnecessary errors and aid in
maximizing your design efforts.
Every so often, there’s a point during the analysis when a novice data-
base developer (and sometimes an experienced one, as well) will stop
and think, “This database doesn’t look too bad. Let’s just end the analy-
sis here and use this database as the basis for the new one.” This is a
particularly bad idea because every hidden problem within the current
database structure will be transferred into the new database. These
types of problems include awkward table structures, poorly defined re-
lationships, and inconsistent field specifications; they will invariably
surface later and at the least opportune times. Therefore, you should do
your best to avoid this perilous situation by following the rule above.
Just remember that it’s always better to define a new database struc-
ture explicitly than to copy an existing structure. After all, if the old da-
tabase didn’t have problems, you wouldn’t be building a new one.
You’ll typically analyze two types of databases during this part of the de-
sign process: paper-based databases and legacy databases. Many orga-
nizations use both types of databases to some degree, and you perform
the same basic analysis process on each of them. There are minor dif-
ferences in the way you analyze a paper-based database and a legacy
database, to be sure, but the differences have more to do with the data-
bases themselves than with the overall analysis process. You needn’t be
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Getting to Know the Current Database 123
concerned with these differences, however, because I’ve seamlessly in-
corporated them into the analysis process presented in this book.
Paper-Based Databases
A paper-based database incorporates data that is literally collected,
stored, and maintained on paper. The paper used in this type of data-
base appears in a variety of shapes, sizes, and configurations. Some of
the more common formats include index cards, hand-written reports,
and various types of preprinted forms. Anyone who has ever worked in
an office for a business or organization is very familiar with this type of
database.
You’ll find that analyzing this type of database can be a daunting task.
One of your most immediate problems is finding someone who com-
pletely understands how the database works so you can learn its use
and purpose. There are several problems with the paper-based database
itself, especially in terms of the way data is collected and managed. This
type of database typically contains inconsistent data, erroneous data,
duplicate data, redundant data, incomplete entries, and old data that
should have been purged from the database long ago. Clearly, the only
reason you’d analyze this type of database is to identify items that you
could incorporate into the new database. For example, you can extract
individual pieces of data from various sections of a form in the paper-
based database and transform them into fields in the new database.
Legacy Databases
A legacy database is a database that has been in existence and in use
for five years or more. Mainframe databases typically fall into this cate-
gory, as do older PC-based databases. There are several reasons that
“legacy” is used as part of the name for this type of database. First, it
suggests that the database has been around for a long time, possibly
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longer than anyone can clearly remember. Second, the word “legacy”
may mean that the individual who originally created the database has
either shifted responsibilities within the organization or is working for
someone else, and, thus, the database has become his or her legacy to
the organization. Third, the term implies the disturbing possibility that
no single individual completely understands the database structure or
how it is implemented in the DBMS software program.
Mainframe legacy databases present some special problems in the anal-
ysis process. One problem stems from the fact that a number of older
mainframe databases are based on hierarchical or network database
models. If neither you nor anyone in the organization has a firm under-
standing of these models, it will take you some time to decipher the
structure of the database. In this case, you’ll find it very helpful to make
printouts of the data in each of the database structures.
Even if a legacy database is based on the relational model, there’s no
particular guarantee that the structure is sound. Unfortunately, there
are many instances where the people who created these databases
didn’t completely understand the concept of a relational database. (After
you have read this book, you won’t fall into that group.) As a result,
many older databases have improper or inefficient structures.
Numerous PC-based legacy databases are improperly or inefficiently de-
signed as well. Many of them were originally designed and implemented in
dBase II and dBase III, which were nonrelational database-management
systems. As a result, the databases implemented within these systems
could not take advantage of the benefits provided by the relational
model. Two characteristics commonly associated with these types of da-
tabases are duplicate fields and redundant data, which (as you’ll learn
later) can cause serious problems with data integrity.
Analyzing a legacy database is somewhat easier than analyzing a paper-
based database because a legacy database is typically more organized
and structured than a paper-based database, the structures within the
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Looking at How Data Is Collected 125
database are explicitly defined, and there is usually a software applica-
tion program that people use to interact with the data in the database.
(The application program is valuable to you during the analysis process
because it can reveal a lot of information about the data structures and
the tasks performed against the data in the legacy database.) The time it
will take you to perform a proper analysis will depend to some degree on
the platform (mainframe or PC), the DBMS used to implement the legacy
database, and the software application program.
The key point to remember when you’re analyzing either a paper-based
or a legacy database is that you should proceed through the process pa-
tiently and methodically so that you can ensure a thorough and accu-
rate analysis.
Conducting the Analysis
There are three steps in the analysis process: reviewing the way data is
collected, reviewing the manner in which information is presented, and
conducting interviews with users and management.
It will be necessary for you to speak to various people in the organiza-
tion as you conduct the first two steps in this process. Be sure your con-
versations relate purely to the reviews at hand. You’ll have the
opportunity to ask them other in-depth questions later. Keep in mind
that these reviews are an integral part of your preparation for the inter-
views that will follow. Indeed, these reviews help you determine the
types of questions you’ll need to ask in subsequent interviews.
Looking at How Data Is Collected
The first step in the analysis process involves reviewing the ways in
which data is collected. This includes everything from index cards and
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hand-written lists to preprinted forms and data-entry screens (such as
those used in a database software program or Web browser).
Begin this step by reviewing all paper-based items. Find out what types of
paper documents the organization is using to record data, and then
gather a single sample of each. Assemble these samples into a stack, and
then store them in a folder for use later in the design process. For exam-
ple, assume that the organization is collecting supplier data on index
cards. Go through each of the index cards until you find one with an entry
that is as complete as possible. When you’ve found an appropriate sam-
ple, make a copy of it and place the copy in your stack of samples. Proceed
through this process for each type of paper record being used. Figure 6.1
shows two examples of how the organization might use a paper record to
collect data.
Figure 6.1. Examples of paper-based items used to collect data.
A1 Office Supplies
Suite 133
7739 Alpine Way SE
Seattle, WA 98115
Susan McLain 519-5883
FAX 519-9948
Employee Fact Sheet
Name: George Chavez
Address: 7527 Taxco Drive
SSN: 456-92-0049Date of Birth: 09/22/55
Date Hired: June 30, 1995
City: Seattle State: WA
Phone: 553-0399
Education: Name of Academic Organization Location Year Graduated
University of Texas at El Paso El Paso, TX 1977
Zip: 98115
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Looking at How Data Is Collected 127
Next, review all of the computer software programs that the organiza-
tion uses to collect data. The objective here is to gather a set of sample
screen shots that represent how the organization uses these programs
to work with data. A word of caution: Many people have discovered
unique and ingenious ways to use common programs, such as word
processors and spreadsheets, as a way to collect and manage data.
Make sure you speak with someone who is familiar with the way the
computers are being used within the organization and determine which
programs the organization is using to manage its data.
As you review each program, find a screen that best represents how
the program collects data. You’re looking for screens similar to those
in Figure 6.2.
Figure 6.2. A typical database screen and a typical spreadsheet screen.
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128 Chapter 6 Analyzing the Current Database
The first screen is typical of those you would find in a database program,
and the second screen is typical of those you would find in a spreadsheet
program. When you’ve found an appropriate sample, create a screen shot
(use [ALT]-[PRTSC] or a screen-capture program), paste it into a docu-
ment in your word-processing program, indicate the name of the source
program and the date you created the screen shot, and then print the
document. Continue reviewing the program and repeat this procedure as
appropriate. Then repeat the entire process for each program. Once
you’ve printed copies of all the appropriate screen shots, assemble them
together and store them in a folder for use later in the design process.
Now examine the Web pages that the organization uses to collect data
via the Internet. The pages you’re interested in will look very similar to
the data-entry forms you would find in a database application program.
Figure 6.3 shows an example of such a page.
Figure 6.3. An example of a typical Web-based data-entry screen.
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Looking at How Information Is Presented 129
You can follow the same examination procedure here that you used with
the application programs. Take a screen shot of a given Web page, paste
it into a word-processing document, indicate the program name and
screen capture date, and print it. Continue to review the Web pages and
repeat this procedure as appropriate. Once you’ve printed copies of all
the appropriate screen shots, assemble them and store them in a folder
for use later in the design process.
Make sure you clearly mark the folders containing the samples you’ve
gathered during your analysis. The small amounts of time you invest to
organize your materials pay big dividends when you use those materials
during a complex phase of the design process.
Looking at How Information Is Presented
The second step in the analysis process involves reviewing the various
ways in which the organization presents its data as information. During
this process, you’ll review items, such as hand-written documents,
computer printouts, screen presentations, and Web pages.
Here are three of the most popular presentation methods that you’ll en-
counter during this process:
1. Reports. A report is any document (hand-written, typed, or
computer-generated) used to arrange and present data in such
a way that it is meaningful to the person or people viewing it.
Although using a software program (such as a word processor
or spreadsheet) is the standard method of generating a report
nowadays, you’ll still find a number of reports written by hand or
typed on a typewriter. (Yes, a typewriter!)
2. Screen presentations (a.k.a. slide shows). This type of presenta-
tion incorporates a series of screens that discuss various topics in
an organized manner. It is generally created with a program, such
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as Microsoft PowerPoint or Lotus Freelance Graphics, and exe-
cuted on a computer, but it can also be composed of a series of
plastic sheets that are displayed on a screen by an overhead pro-
jector. (For our purposes, we’ll assume that you’re reviewing a
computer-based screen presentation.)
3. Web pages. Many organizations are now making vast amounts of
information available via Web pages on their Web sites. A Web
page is used much in the same manner as a report, and, indeed,
it is really nothing more than a different type of report.
Begin this step by identifying and reviewing each report the organiza-
tion generates from the database, regardless of whether they produce
the report by hand or from within a software program. Gather samples
of the reports and assemble them in a folder as you did with the items
in the previous step. Overall, this task is easier to perform in this step
than it was in the previous step because people in the organization are
typically familiar with the reports they use. Copies of the reports are
usually readily available, and most reports can be reprinted if neces-
sary. Figure 6.4 shows an example of a report written by hand and a re-
port generated from a word-processing program.
Next, review screen presentations that use or incorporate the data in
the database. It’s unnecessary for you to review every presentation,
but you do need to review those that have a direct bearing on the data
in the database. For example, you don’t need to review a presentation
on the organization’s new product if it doesn’t draw any data from the
database. On the other hand, a presentation on sales statistics that
does incorporate data from the database is one that you do need to
review.
Once you’ve identified which presentations you need to review, go
through each one carefully and make screen shots of the slides that use
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Looking at How Information Is Presented 131
or incorporate data from the database. Copy the screen shots into a
word-processing document, print the document, and then store the doc-
ument in a folder for later use. (Write the name of the presentation and
the date you captured the screen shots on the folder; you may need to
refer to it again at a later time.) Follow this procedure separately for each
presentation. You want to make sure you don’t accidentally combine two
or more presentations together, because this mistake will inevitably lead
to mass confusion and result in one huge mess!
Employee Phone List as of 05/16/96
John Alcot 554-3002
Regina Allen 752-5593
George Chavez 623-3292
Ryan Erlich 554-2991
Product ID
9001
9002
9003
9004
Current Product Inventory
Product Description
Shur-Lok U-Lock
SpeedRite Cyclecomputer
SteelHead Microshell Helmet
SureStop 133-MB Brakes
Category
Accessories
Accessories
Components
SRP
75.00
65.00
36.00
23.50
Quantity
20
33
16
Figure 6.4. Examples of hand-written and computer-generated reports.
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132 Chapter 6 Analyzing the Current Database
Figure 6.5 shows an example of the type of slides you’ll examine during
this review.
Reviewing a presentation is difficult in some cases, and deciding
whether or not a slide should be included as a sample is purely a dis-
cretionary decision. Therefore, work closely with the person most famil-
iar with the presentation to ensure that you include all appropriate
slides in the samples.
Finally, review Web pages that draw information directly from the data-
base. Perform this review in the same manner as the review for the
screen presentations. As with the previous review, you need to review
those Web pages that have a direct bearing on the data in the database.
For example, you don’t need to review a Web page that provides a his-
tory of your organization, but you do need to review a Web page that dis-
plays regional employee information.
Once you’ve identified which Web pages you need to review, take a
screen shot of each page. Copy the screen shots into a word-processing
document, print the document, and then store the document in a folder
Central
Northeast
Pacific NW
Southern
Western
1st Qtr
235
335
229
315
240
2nd Qtr
277
369
277
345
251
3rd Qtr
289
388
300
365
266
4th Qtr
316
359
315
376
289
2003 Regional Sales
Total Units Sold per Quarter
Total Orders Delivered
per Shipper
1 2 3 4 5 6 7 expressed in 100s
Aero-Xpress
Global
Postal Express
Figure 6.5. Examples of screen presentation slides.
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Conducting Interviews 133
for later use. (Write the uniform resource locator, or URL, address, and
the current date under each screen shot in the document; you may
need to refer to a particular Web page again at a later time.)
Figure 6.6 shows an example of a Web page you would examine during
this review.
Whenever possible, work with the person (or persons) who created and
developed the organization’s Web site. She can save you a lot of time by
directing you to the exact pages you should examine for this review.
Conducting Interviews
Now that you have a general idea of how the organization collects
and presents its data, it’s time to interview users and management
Figure 6.6. Example of a Web page that presents information from a database.
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134 Chapter 6 Analyzing the Current Database
to determine how the organization uses its data. Interviews are useful
in the analysis phase for these reasons:
• They provide details about the samples you assembled during the
previous reviews. The discussions you had with users and man-
agement during the previous reviews were solely meant to
identify (in general terms) how the organization collects and pre-
sents the data it uses. In this phase, however, you’ll ask specific
questions about the samples you assembled during those
reviews. This will enable you to clarify the aspects of a specific
sample that you consider to be vague or ambiguous.
• They provide information on the way the organization uses its
data. These interviews will provide you with information on how
users work with the organization’s data on a daily basis and how
management uses information based on that data to manage the
organization’s affairs.
• They are instrumental in defining preliminary field and table struc-
tures. The responses you receive from users and management
during this round of interviews will help you identify initial field
and table structures for the database.
• They help to define future information requirements. The discus-
sions you’ll have with users and management regarding the
organization’s future growth will often reveal new information
requirements that must be supported by the database.
I cannot overemphasize, and you must not underestimate, the impact
interviews have on the final database structure and how important they
are to your successful completion of the database-design process. Only
full and complete interviews will help you ensure that the database you
design fulfills your organization’s information requirements.
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Conducting Interviews 135
Basic Interview Techniques
In order for you to conduct successful interviews, you must first learn a
few basic interview techniques. I address this issue here by providing
you with a set of fundamental techniques that you can use to conduct
every interview within the database-design process. These techniques
are relatively easy to learn and apply, and they’ll enable you to obtain
the information you require for the task at hand.
You’ll probably execute these techniques in a strict, mechanical fashion
as you’re just starting to learn them, but you’ll apply them more in-
stinctively and intuitively as you conduct further interviews and gain
additional experience. Conducting an interview is a skill, and, as with
any other skill, you will achieve various degrees of expertise with pa-
tience and practice.
Asking Questions
You use both open-ended and closed questions throughout an inter-
view, alternating between each type as the interview progresses; the
open-ended questions enable you to focus on specific subjects, and the
closed questions allow you to focus on specific details of a certain sub-
ject. For instance, start the interview with a few open-ended questions
to establish some general subjects for discussion, and then select a
subject and ask more specific (closed) questions relating to that subject.
You could begin by asking one of the interview participants an open-
ended question such as this:
“How would you define the work that you do on a daily basis?”
Most participants will use three or more sentences to answer this type
of question. It’s perfectly acceptable for a participant to provide you
with a long, descriptive response because you can work with this type
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of response more easily than you can with one that is terse. To illus-
trate this point, assume the participant responds to your question in
this manner:
“As an account representative, I’m responsible for 10 clients.
Each of my clients makes an appointment to come into the
showroom to view the merchandise we have to offer for the cur-
rent season. Part of my job is to answer any questions they have
about our merchandise and make recommendations regarding
the most popular items. Once they make a decision on the mer-
chandise they’d like to purchase, I write up a sales order for the
client. Then I give the sales order to my assistant, who promptly
fills the order and sends it to the client.”
This is a very good response. The participant not only answered your
question, but also provided you with the opportunity to begin asking
follow-up questions. His response also suggests several subjects that
you can discuss later in the interview.
Identifying Subjects
As you ask each open-ended question, identify the subjects suggested
within the response to the question. You can identify subjects by look-
ing for nouns within the sentences that make up the response. Subjects
❖ Note When you receive a terse response such as “I fill out cus- tomer sales orders,” you’ll have to work a little harder with the
participant to obtain the information you need. Terse responses
commonly indicate that the participant is just nervous or uncom-
fortable. In this case, you could put him at ease by discussing an
unrelated topic for a few moments, or by allowing him to select a
more familiar or comfortable subject.
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Conducting Interviews 137
are always represented by nouns and identify a person, place, or thing
or an event (something that occurs at a given point in time). There are
some nouns, however, that represent a characteristic of a person, place,
or thing or event; you don’t need to concern yourself with these just yet.
Therefore, make sure you only look for nouns that specifically represent
a person, place, or thing or event. You can ensure that you account for
every subject you need to discuss by marking the nouns with a double-
underline as you identify them, as in this example:
“As an account representative, I’m responsible for 10 clients.
Each of my clients makes an appointment to come into the
showroom to view the merchandise we have to offer for the cur-
rent season. Part of my job is to answer any questions they have
about our merchandise and make recommendations regarding
the most popular items. Once they make a decision on the mer-
chandise they’d like to purchase, I write up a sales order for the
client. Then I give the sales order to my assistant, who promptly
fills the order and sends it to the client.”
After you’ve identified all of the appropriate nouns within the response,
list them on a sheet of paper; this becomes your list of subjects. You’ll
add more subjects to the list as you continue to work through the de-
sign process. Compile this list carefully and methodically because you’ll
use it to generate further discussions as the interview progresses and to
help you define tables later in the design process.
Here are subjects that are represented in the previous response:
Account Representative
Appointment
Assistant
Clients
Items
Job
Merchandise
Sales Order
Season
Showroom
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You can now use this list as the basis of further questions during the
interview.
Verify that the nouns you’ve underlined are genuine subjects by review-
ing the way they’re used in the response. For example, “account repre-
sentative” is a subject suggested by a noun in the first sentence, and
you can assume that the subject identifies an object (person, place, or
thing) by the way the noun is used in the sentence. “Appointment” is
another subject suggested by a noun in the second sentence, and you
can assume this subject represents an event (something that occurs at
a given point in time) by the way it is used in the sentence.
Identifying Characteristics
After you’ve identified the subjects suggested within the response, pick
a particular subject and begin to ask follow-up questions related to that
subject. You use this line of questioning to obtain as much detailed in-
formation as possible about the subject you’ve selected. Therefore,
make your follow-up questions more specific as you progress through
this part of the discussion. The nature of your follow-up questions will
depend on the responses you receive from the participant. Based on our
sample response, for example, you could continue the discussion by
asking more specific questions about sales orders, or you could begin
an entirely new line of questioning regarding clients. Assume, for now,
that you ask the following question to learn more about sales orders:
“Let’s discuss sales orders for a moment. What does it take to
complete a sales order for a client?”
Note that this question begins with a statement directing the interview
participant to focus on a particular subject. This is a technique you
❖Note I refer to this entire procedure as the subject-identification technique throughout the remainder of the book.
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Conducting Interviews 139
should use to guide your conversation after you’ve selected a specific
subject to discuss. Also note that the question is open-ended; it prompts
the participant for details related to the subject you’ve selected (sales
orders) and allows you to establish the focus of the participant’s subse-
quent responses.
Now, assume that the participant gives the following reply:
“Well, I enter all the client information first, such as the client’s
name, address, and phone number. Then I enter the items the
client wants to purchase. After I’ve entered all the items, I tally
up the totals and I’m done. Oh, I forgot to mention: I enter the
client’s fax number and shipping address—if they have one.”
Analyze this response with the subject-identification technique to deter-
mine whether there are subjects suggested within the response. Then
add the new subjects to your list of subjects. Remember: List only those
nouns that represent person, place, or thing or event.
After you’ve finished identifying new subjects, begin looking for details
regarding the subject under discussion. Your objective here is to obtain
as many facts about the subject as possible. Now you’re interested in
nouns that represent characteristics of a subject—they describe particu-
lar aspects of that subject. You can identify these nouns quite easily be-
cause they are usually in singular form (“phone number,” “address”). In
contrast, nouns that identify subjects are usually in possessive form
(“the client’s phone number,” “the company’s address”).
Try to account for as many characteristics of the subject as possible.
Use a single underline to mark a noun that represents a characteristic,
as in this example:
“Well, I enter all the client information first, such as the client’s
name, address, and phone number. Then I enter the items the
client wants to purchase. After I’ve entered all the items, I tally
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140 Chapter 6 Analyzing the Current Database
up the totals and I’m done. Oh, I forgot to mention that I enter
the client’s fax number and shipping address—if they have one.”
As you identify the appropriate nouns within a response, list them on a
sheet of paper; this becomes your list of characteristics. You’ll add more
characteristics to the list as you work through the design process, and
you’ll use this list later when you’re determining the fields for the data-
base. Use a separate sheet of paper for the list of characteristics. Do not
list the subjects and characteristics on the same sheet! (The reason for
keeping them on different lists will become clear when you begin to de-
fine tables for the database in Chapter 7.)
Here are the characteristics (shown in alphabetical order) that are rep-
resented in the previous response:
This constitutes the list of characteristics for the subject under discus-
sion. These characteristics will eventually become fields in the database.
Verify that the nouns you’ve marked with a single underline are genuine
characteristics by reviewing the way they’re used in the response. For
example, “name,” is a characteristic suggested by a noun in the first
sentence, and you can assume that it describes some aspect of the sub-
ject “Client” by the way the noun is used in the sentence. “Shipping ad-
dress” is another characteristic suggested by a noun in the last
Address
Fax Number
Name
Phone Number
Shipping Address
Totals
❖ Note I refer to this entire procedure as the characteristic- identification technique throughout the remainder of the book.
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Conducting Interviews 141
sentence, and you can assume that this noun also represents some as-
pect of the subject “Client” by the way the noun is used in the sentence.
After you’ve finished discussing a particular subject, move on to the
next subject on your subjects list and begin the same pattern of ques-
tioning. Start with open-ended questions, identify the subjects sug-
gested in the responses, ask more specific questions as the discussion
progresses, and identify as many of the subject’s characteristics as pos-
sible. Continue this process in an orderly manner until you’ve dis-
cussed every subject on your list.
You should learn the subject-identification technique and the
characteristic-identification technique as thoroughly as possible because
you’ll use them during your interviews with users and management and
as you identify fields and tables for the initial database structure. Note
that you won’t have to incorporate the single and double underlines for-
ever; you’ll eventually execute these techniques in your mind as you gain
experience and as they become more instinctive and intuitive.
Before You Begin the Interview Process . . .
You can use the techniques you’ve just learned in this section for both
user interviews and management interviews. The only differences
between the two sets of interviews lie in the subject matter and the
content of the questions.
The interview process involves two sets of discussions: one with users
and the other with management. You’ll speak to the users first because
they represent the “front lines” of the organization. They have the clear-
est picture of the details connected with the organization’s daily opera-
tions. Also, the information you gather from the users should help you
to understand the answers you receive from management.
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Interviewing Users
The first part of the interview process involves conducting user inter-
views. The interviews focus on these four issues:
1. The types of data users are currently using
2. How users are currently using their data
3. The collection of samples you assembled during the first two steps
of the analysis
4. The types of information users require for their daily work
Because these issues are both data-centric and information-centric,
you must be certain that you understand and always keep in mind the
difference between data and information. Recall from Chapter 3 that
data are the values you store in the database, and information is data
that you process in a manner that makes it meaningful and useful to
you when you work with it or view it. Keeping these definitions in mind
will help ensure that you focus on each issue properly and conduct
each segment of the interview successfully.
Reviewing Data Type and Usage
You can usually discuss the first two issues at the same time if you care-
fully phrase your questions at the beginning of the interview. Your objec-
tive for this part of the interview is to identify the types of data the users
are currently using and how they use that data in support of the work
they do. You’ll use this information later in the design process to help de-
fine field and table structures. Use the data-collection and data-represen-
tation samples to help you formulate questions about the user’s data.
(However, don’t actually discuss the samples just yet; you should deal
with them separately.) During this discussion, you’ll start with open-
ended questions, identify subjects within the responses, and then use
specific follow-up questions to identify the characteristics of each subject.
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As you begin the interview, ask each participant about the work he or
she performs on a daily basis. After the participant provides an overall
description of the work he does, ask him to explain his job in more de-
tail. Perhaps he can walk you through the job he performs on a daily
basis.
Here’s an example of a typical conversation that occurs during this part
of the interview:
INTERVIEWER: “What kind of work do you do on a day-to-day
basis?”
PARTICIPANT: “I accept land-use applications that are submit-
ted by various people, log them in, and set a
hearing date with the hearing examiner. I also
assist applicants if they have any questions
regarding a specific application.”
INTERVIEWER: “Let’s talk about the applications for a moment.
What types of facts are associated with an
application?”
PARTICIPANT: “There’s quite a number, actually. There are facts
concerning the type and name of the application,
its designation and address, and its location.”
INTERVIEWER: “Tell me about the facts concerning the applica-
tion’s type and name.”
PARTICIPANT: “There are four things we record: the type of appli-
cation, the name of the subdivision, the purpose
of the project, and a description of the project.”
Note how the interviewer starts the discussion with an open-ended
question. After the participant responds, the interviewer uses the sub-
ject-identification technique to identify subjects within the response. The
interviewer then chooses a particular subject and uses another open-
ended question to focus the participant’s attention on that subject.
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Because the participant’s next response is general in nature, the inter-
viewer focuses on a particular aspect of the subject and uses a more spe-
cific follow-up question to elicit a detailed response from the participant.
The interviewer can continue to narrow the focus of his questions as the
discussion progresses. As the participant responds to each question,
the interviewer continues to use the characteristic-identification tech-
nique to identify characteristics of the subject that appear in the re-
sponse. After he’s identified all of the subject’s characteristics, the
interviewer then moves on to the next subject and begins the entire pro-
cess again. He’ll continue in this manner until he’s covered his entire
list of subjects. You’ll go through the same exact process when you act
as interviewer.
Reviewing the Samples
The next round of discussions centers on all the samples you assembled
earlier in the analysis process. Your objectives during these discussions
are to identify how the objects represented by the samples are used, to
clarify the aspects of the samples you don’t understand, and to assign a
description to each sample.
It should be relatively easy for you to talk to participants about the sam-
ples now that you have an idea of the data the participants use on a
daily basis. Begin the conversation by asking questions about a specific
sample. Figure 6.7 shows an example of a data-collection sample you
might use as a starting point.
Review your notes from the discussions you held at the beginning of the
interview before you ask your first question. You want to determine
whether anything you’ve already discussed is relevant to the sample
you’re about to discuss. In one of the previous discussions, for example,
a participant indicated that part of his job is to keep track of all the or-
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Interviewing Users 145
ganization’s customers. Using that statement as a starting point, you
could ask him how he uses this particular data-collection sample to
perform that task.
“You mentioned in a previous discussion that you keep track of
all the customers. How does this screen help you to carry out
that task?”
This is a well-phrased question. It begins with a statement that focuses
on a particular subject and then continues by bringing the participant’s
attention to the sample. The question is open enough to elicit a clear
and complete response.
Now, assume the participant provides this response:
“This screen allows me to enter new customers, as well as modify
and maintain all the information we have on existing customers.”
If this reply answers the question to your complete satisfaction, use
it as the basis for a description of the sample. On the other hand, if
Mike's Bike Shop
File Edit View Insert Format Records Tools Window Help
Customer Information
Name (F/L):
Address:
City:
State: Zip:
John
TX 79915
725 Globe Circle
El Paso 778-9715
778-4497
Active
Phone:
FAX:
Status:
Edit< Back Next > Save
Figure 6.7. A data-collection sample.
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146 Chapter 6 Analyzing the Current Database
the reply does not completely answer the question, continue with an
appropriate line of questioning until the participant clearly identifies
the purpose and use of the sample. You must supply descriptions for
all of your samples because you’ll use them again later in the design
process.
A sample’s description should be succinct, yet clear enough to indicate
the sample’s purpose and how it is used. Write the description on a slip
of paper and attach it to the sample. Here’s an example of a description
you might use for the sample in Figure 6.7:
This screen is used to collect and maintain all customer data.
It’s necessary for you to understand the sample as completely as possi-
ble so that you can write a clear and concise description. If there are as-
pects of a given sample you don’t understand, ask the participant to
clarify them for you. For example, assume you’re working with the re-
port sample shown in Figure 6.8.
Product ID
9001
9002
9003
9004
Current Product Inventory
Product Description
Shur-Lok U-Lock
SpeedRite Cyclecomputer
SteelHead Microshell Helmet
SureStop 133-MB Brakes
Category
Accessories
Accessories
Components
SRP
75.00
65.00
36.00
23.50
Quantity
20
33
16
Figure 6.8. A report sample.
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Interviewing Users 147
If you don’t know what the abbreviation “SRP” represents, ask someone
to tell you what it means. A simple question such as this will often clar-
ify the issue:
“What do the letters ‘SRP’ represent in the ‘Current Product
Inventory’ report?”
As you compose descriptions for each of the samples, you might find it
difficult to write a description for a complex sample. A sample is complex
if it represents more than one subject. The sample in Figure 6.8, for ex-
ample, covers only one subject: products. The sample in Figure 6.9, how-
ever, covers at least three subjects: doctor services, nursing services, and
patients. You’ll often have to work a little harder to determine a complex
sample’s purpose and use. In some cases, you’ll have to use the subject-
identification technique to determine what subjects are represented
Eastside Medical Clinic 7743 Kingman Dr. Seattle, WA 98032
(206) 555-9982
Patient Name: George Edelman Patient ID: 10884
Visit Date: 05/16/96 Physician: Daniel Chavez
Doctors Services Service Code Fee
X X
Consultation
EKG
Physical
Ultrasound
92883
92773
98377
97399
119.00
95.00
Nursing Services Service Code Fee
R.N. Exam
Supplies
Nurse Instruction
Insurance Report
89327
82372
88332
81368
Figure 6.9. An example of a complex report sample.
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148 Chapter 6 Analyzing the Current Database
within the sample. Once you’ve identified the subjects, it will be easier for
you to clarify the function or functions of the sample. You can then com-
pose a description that gives a clear picture of the sample’s purpose.
Let’s say you’re working with the report sample shown in Figure 6.9 and
you have questions regarding the nursing services. You wonder whether
the organization is using this report as an indirect means of maintain-
ing a current list of nursing services. A question that elicits a yes or no
response from a participant is not going to help you much at all, so you
need to use an open-ended question that will elicit a more informative
response. You could begin your discussion of this sample with this
question:
“What nursing services do you provide besides those listed in
this sample?”
This type of question gives the participant an opportunity to provide you
with a detailed response; furthermore, you’ve given yourself the oppor-
tunity to ask follow-up questions as warranted by the participant’s re-
ply. To continue the example, say you receive the following answer:
“We provide various specialized services for the more complex
patient. You see only the general services on this report. How-
ever, I can show you a complete list of our services that
Katherine maintains on her computer.”
You can continue with the process of writing the sample’s description if
this reply clarifies the point in question and you now understand the
purpose of this report sample; otherwise, continue asking follow-up
questions until everything is explained to your satisfaction.
Reviewing Information Requirements
The final issue you’ll discuss with users concerns their information re-
quirements. The objectives of this discussion are to determine whether
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Interviewing Users 149
individual users receive information based on data they don’t directly
control or maintain, to determine what types of additional information
they need, and to determine what types of information they can foresee
themselves needing in the future. You’ll use the information you gather
during this discussion later in the design process to help define and ver-
ify field and table structures. You can also use this information as yet
another way of determining whether you accidentally overlooked any-
thing during the previous discussions.
Current Information Requirements
Users typically receive the information they use through a variety of re-
ports. Therefore, the best way to begin this discussion is by reviewing
the report samples. This time around, though, you’re not so concerned
with how the reports are used as you are with the data upon which they
are based. It’s quite common that information on some of the reports a
user receives is based on data he does not personally create and main-
tain. In this situation, you must determine the origin of that data so
that you can identify all the data used by a user, whether he uses it di-
rectly or indirectly.
Select a report from the report samples and work with one of the partic-
ipants to determine what data is used to produce the report. Ask him if
he creates and maintains the data on which the report is based. You
can move on to the next sample if he answers yes, but you’ll need to
identify the origin of the data if he answers no. Here’s an example that
illustrates this process.
Say you have an assistant named Kendra who is beginning a discussion
with a participant named Joyce regarding the report sample shown in
Figure 6.10.
As Kendra begins the conversation, Joyce mentions that she works in
the telemarketing department. When Kendra first asks about the sample
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150 Chapter 6 Analyzing the Current Database
report, Joyce indicates that she receives it every Monday morning. So
Kendra asks her the following question:
“Do you provide the data that’s used to generate this report?”
Her next course of action depends on Joyce’s response. Kendra can
move on to the next sample if Joyce’s answer is yes; however, it would
be a good idea for Kendra to ask a follow-up question to make certain
that Joyce’s answer is true.
“Do you personally enter and maintain this data on a daily
basis?”
If Joyce’s answer is still yes, Kendra can definitely move on to the next
sample.
On the other hand, if Joyce’s answer to the original question is no, Ken-
dra will need to ask a few follow-up questions. First, she’ll ask Joyce
whether she contributes any data to the report. If she does, Kendra will
then determine what data Joyce specifically submits. Then Kendra will
ask whether or not Joyce knows the source of the remaining data.
Last Purchase
05/21/96
03/19/96
05/16/96
04/12/96
Customer Type
Preferred
Silver
Preferred
Gold
Customer Name
Alastair Black
Dave Cunningham
Zachary Ehrlich
Frank Lerum
Phone Number
551-0993
533-9182
515-3921
552-3884
Customer Phone List
Figure 6.10. A sample report.
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Interviewing Users 151
To continue the example, say Joyce’s reply to the original question is no
and that the following dialog takes place after her response:
KENDRA: “Can you tell me, then, if there is any data that you con-
tribute to the report at all?”
JOYCE: “I do supply the customer’s name and phone number.”
KENDRA: “Then you don’t supply the customer type or the last pur-
chase date. Is that correct?”
JOYCE: “Yes.”
KENDRA: “Can you tell me who provides this data?”
JOYCE: “I’m not really sure, but . . .”
KENDRA: “Do you have an idea of where these items come from?”
JOYCE: “As a matter of fact, I do. They come from the sales
department.”
KENDRA: “That sounds good to me. I’ll make a note of that on this
sample, and then we can move on to the next one.”
Note that as the dialog begins, Kendra first tries to determine whether
Joyce submits any data at all to the report. When Joyce reveals that she
contributes two of the items for the report, Kendra then poses a follow-
up question to verify that Joyce is not submitting any of the other data.
Finally, Kendra tries to identify the source of the remaining data by ask-
ing Joyce if she knows from where the data originates. In this case, it
takes only two well-phrased questions to find the answer. If Joyce could
not answer the last two questions, Kendra would need to continue her
investigation with other participants.
You’re sure to obtain all the information you need about your report
samples if your discussions progress in the same manner as the preced-
ing dialog. Remember: Follow-up questions are a crucial part of the con-
versation. You must phrase your questions properly to elicit the types of
responses you need from the participants.
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152 Chapter 6 Analyzing the Current Database
Additional Information Requirements
The next subject of discussion is additional information requirements.
The objective here is to determine whether users require additional in-
formation that is not being delivered to them currently. If this is the
case, you must identify what additional information they require and
then define new data structures to support this extra information later
in the design process.
Start this conversation by directing the participants to review the re-
ports they currently receive. Ask them whether there is other informa-
tion they would like to see in their reports. Next, direct them to discuss
the additional information, which reports the information will affect,
and the reason they believe the information is necessary. Then deter-
mine whether the additional information represents new subjects or
new characteristics. If it does, identify each new item and add it to the
appropriate list. Finally, review the participants’ comments and deter-
mine whether there are further issues you need to discuss with them in
regard to the reports. Here’s an example that illustrates the process.
Say you’re beginning this discussion and you’ve just asked the partici-
pants to review the report samples they currently use. One of the partic-
ipants is reviewing the sample report shown in Figure 6.11.
Product ID
Current Product Inventory
Product Description Category SRP
9001 Shur-Lok U-Lock Accessories 75.00
Quantity
9002 SpeedRite Cyclecomputer 65.00 20
9003 SteelHead Microshell Helmet Accessories 36.00 33
9004 SureStop 133-MB Brakes Components 23.50 16
Figure 6.11. The sample report being reviewed by a participant.
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Interviewing Users 153
You now instruct this particular participant to note the additional infor-
mation she would like to see on the reports and to provide a brief state-
ment indicating why the information is necessary. It doesn’t really
matter exactly how she makes the notations so long as they are clear
and attached to the report in an obvious manner. In this case, she de-
cides to use large sticky notes as a means of documenting her com-
ments. She’s specified two new fields she’d like to add to the report,
along with the reason for their inclusion. She’s also suggested possible
locations for the fields by writing their names on the report itself.
Figure 6.12 shows the sample report with her comments.
Next, determine whether there are new subjects or new characteristics
represented in the additional information. Examine each report and
apply the subject-identification technique and the characteristic-
identification technique to the comments attached to the report. Here’s
an example of how you apply these techniques to the first comment in
Figure 6.12:
“Can we include the vendor name? It would make it easier to
identify a specific product.”
Product ID
Current Product Inventory
Product Description Category SRP
9001 Shur-Lok U-Lock Accessories 75.00
Quantity
9002 SpeedRite Cyclecomputer 65.00 20
9003 SteelHead Microshell Helmet Accessories 36.00 33
9004 SureStop 133-MB Brakes Components 23.50 16
Wh ole
sal e C
ost
If we
cou ld
see wh
ole sal
e
cos t, i
t w oul
d h elp
us
cal cul
ate m
ore ac
cur ate
dis cou
nts .
Vend or N
ame
Can we
inclu de th
e Ve ndor
nam e? I
t wo uld
mak e it
easie r to
iden tify
a sp ecifi
c
prod uct
Figure 6.12. A report sample with a participant’s comments.
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154 Chapter 6 Analyzing the Current Database
Here you’ve identified both a subject and a characteristic. (Note that the
subject and characteristic aren’t directly related: “vendor name” is a
characteristic of a vendor, not of a product. There’s no problem here,
but you should be aware that this apparent mismatch of subjects and
characteristics is typical. You’ll address this issue later in the design
process.) Now, check your subjects list and characteristics list to deter-
mine whether you’ve already accounted for these items. If you have,
move on to the next comment and repeat this procedure.
If you do discover a new subject, add it to your list of subjects and then
identify as many of its characteristics as possible. When you’re finished,
add these items to your list of characteristics, move on to the next com-
ment, and repeat the entire procedure. In many instances, however,
you’ll only identify new characteristics. Don’t be alarmed. People often
want to add items to a report that are characteristics of subjects that
are already represented by the information on the report.
Finally, re-examine each report and determine if you have questions or
concerns about the notes participants have made. For instance, you
may question the rationale behind one participant’s belief that specific
fields are necessary on a given report. Or you might wonder why an-
other participant wants to exclude certain fields from one of his reports.
You definitely want to make sure that the fields he wants to exclude are
truly unnecessary and that removing them will not have an adverse ef-
fect on the information the report provides to other people. In either
case, the inclusion or exclusion of fields will affect the final database
structure.
If a report has one or more remarks that are cause for concern, review it
with the appropriate participant and settle as many of the issues as you
can. You can usually resolve all your concerns with a few simple ques-
tions, but in some cases the resolution to certain issues will not become
apparent until later in the design process. For example, you might have
noticed that certain fields appear on two or more reports. It’s difficult to
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Interviewing Users 155
determine if the fields are being unnecessarily duplicated until you be-
gin to define the field and table structures. When you encounter an is-
sue that is difficult to resolve at the present time, make a note of it and
put the report aside for later review.
Future Information Requirements
The last subject of discussion concerns future information require-
ments. Your objective here is to identify the information that the partic-
ipants believe will be necessary for them to receive as the organization
evolves. Once you identify these future information requirements, you
can ensure that you define the data structures necessary to support
that information.
You first need to make sure that every participant has some idea of how
the organization is evolving. The nature of the organization’s evolution
will determine what new information participants will require. If several
people are unacquainted with these issues, you’ll need to obtain this in-
formation from management and then relay it to the participants prior
to the discussion. Once everyone is familiar with these matters, you can
begin the conversation.
Start the discussion by directing the participants to think about the fu-
ture evolution of the organization and how it may affect the work they
do on a daily basis. You’ll often find that some participants are going to
have a difficult time envisioning this scenario. When this happens, use
questions such as these to help them focus their thoughts:
How will the organization’s evolution affect the amount of infor-
mation you’ll need to do your job?
Do you think you’ll need additional types of information to carry
out your duties effectively as the organization evolves?
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156 Chapter 6 Analyzing the Current Database
How will the evolution of the organization increase the time you
spend on your daily tasks?
Can you predict what types (categories, not specific items) of
new information you’ll need in order to carry out your duties as
the organization evolves?
Do you anticipate a need for new information if your duties are
increased as a result of the organization’s evolution?
Keep in mind that most of the participants’ answers will be based on
speculation. There’s no accurate way for them to predict what types of
information they’ll really need until the organization’s evolution occurs.
However, if you can anticipate their hypothetical information require-
ments, you can prepare for them by defining the necessary data struc-
tures in advance.
As the participants respond, use the subject-identification technique to
identify brand-new subjects and then add them to your list of subjects.
Then use the characteristic-identification technique to uncover new de-
tails concerning existing or new subjects and add them to your list of
characteristics.
You can sketch ideas for new reports or data-entry forms to help partic-
ipants visualize the types of information they may need in the future.
These sketches can then help you identify new subjects or characteris-
tics that the database structure needs to address. If you create several
rough drawings of sample reports, be sure to assemble them in a sepa-
rate, clearly marked folder. Then code each revision so that you can
compare it with earlier revisions. Figure 6.13 shows an example of a
preliminary design for a future report.
Continue the conversation with users until you’re satisfied that you’ve
accounted for as many of the participants’ future information require-
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Interviewing Management 157
ments as possible. When you’ve completed the discussion, you’re ready
to conduct interviews with management.
Interviewing Management
The second part of the interview process involves interviewing manage-
ment personnel. This round of interviews focuses on these issues:
1. The types of information managers currently receive
2. The types of additional information they need to receive
❖ Note You can use all of the techniques you learned in this sec- tion for the management interviews as well. Therefore, the next
section is somewhat shorter and more concise.
1st Quarter Customer Sales Statistics
Customer ID
9001
9002
9003
9004
Customer Name
Stewart Jameson
Shannon McLain
Estela Pundt
Timothy Ennis
Maximum Minimum Average Sales Amounts
23.00
125.00
35.00
20.00
55.00
70.00
36.00
25.00
265.00
550.00
250.00
325.00
Figure 6.13. An example of a design for a new report.
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158 Chapter 6 Analyzing the Current Database
3. The types of information they foresee themselves needing
4. Their perception of the organization’s overall information
requirements
Reviewing Current Information Requirements
Your objectives during the first part of this interview are to identify the
information that management routinely receives and to determine
whether it receives reports that are not represented in your group of re-
port samples.
As you begin the interview, ask each participant about the work he per-
forms and the responsibilities associated with his position. A manager
typically has a number of issues on his mind, so these questions will help
him focus his attention on the matters at hand. His answers will give you
some idea of how he might use the information on the reports he receives
and will provide you with a perspective on his need for that information.
Next, ask each participant if he uses any of the reports in your collection
of report samples. Proceed with the next step if he says he doesn’t use
any of the reports; otherwise, examine each report and ask him to help
you identify other subjects that you might have previously overlooked.
Use the subject-identification technique as necessary to aid you in this
process. If the manager identifies a new subject, add it to your list of sub-
jects and use the characteristic-identification technique to determine the
subject’s characteristics. Then add the new characteristics to your list of
characteristics. Repeat this entire procedure for each sample report.
❖ Note Throughout the remainder of the book, I use the term management to refer to the person or persons controlling or
directing the organization.
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Interviewing Management 159
Continue the discussion by asking each participant whether he receives
reports that are not represented in your report samples. If he answers
yes, obtain a sample of each new report and review it with the partici-
pant. Use the subject-identification technique and the characteristic-
identification technique to identify the subjects (and their associated
characteristics) represented within the report and then add the subjects
and characteristics to their respective lists. Finally, attach a description
to the report and add it to your collection of report samples. Repeat this
procedure until you’ve accounted for every new report.
Reviewing Additional Information Requirements
The next subject of discussion concerns management’s need for addi-
tional information. Your objective is to determine whether it requires
supplemental information that is currently missing from the reports it
receives. If you conclude that this is the case, you must identify that ad-
ditional information. You’ll then define new data structures (as appro-
priate) to support this information later in the design process. However,
you can move on to the next part of the interview if management doesn’t
require additional information.
You use the same techniques for this discussion as those you used for
this segment of the user interviews. Here are the steps you’ll follow:
1. Review the report samples with the participants once again and
ask them if there is additional information they would like to
include in any of the reports.
2. Have the participants note the additional information—including
the reasons that they believe it’s necessary—on the appropriate
reports. Remember that it doesn’t matter how the participants
make the notations so long as they are clear, noticeable, and are
attached to the appropriate report.
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3. Identify new subjects or characteristics within the information
and add them to the appropriate list.
4. Review the reports and discuss any concerns you have about
them with the participants. Once your concerns are resolved, this
process is complete.
Reviewing Future Information Requirements
Future information requirements are the next subject of discussion.
Your objective here is to determine what information management fore-
sees itself needing in the future. Once you’ve identified these require-
ments, you can ensure that there are data structures in place to support
this information as the need for it arises.
As you begin the discussion, have the participants consider how the or-
ganization is currently evolving. Then ask them how this evolution will
affect the information they require to make sound decisions and how it
will influence the way they guide or direct the organization. Remember
that their answers are going to be based on speculation, as was the case
with the similar questions you asked users; there’s no way for manage-
ment to predict its future needs accurately until the organization actu-
ally begins to evolve. (It’s always a good idea, however, to plan for the
future as much as possible.) Use the subject-identification technique
and characteristic-identification technique to identify new subjects and
characteristics within the participants’ responses and then add the new
items (if any) to the appropriate lists.
Next, make sketches of any new reports the participants might have in
mind. Identify new subjects and characteristics within each report and
add them to the appropriate lists. Then assemble these new reports in a
clearly marked folder and add it to your collection of samples.
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Interviewing Management 161
You’re ready to move on to the last subject when you’ve accounted for as
many of management’s future information requirements as possible.
Reviewing Overall Information Requirements
The last topic of discussion concerns the organization’s overall informa-
tion requirements. In management’s opinion, what generic class of in-
formation does the organization need? Your objective here is to discover
whether there is data that the organization needs to maintain that has
not been previously discussed in either the user interviews or the man-
agement interviews. If you determine that there is such data, you must
account for it in the database structure.
Take all of the reports that you’ve gathered throughout the analysis
and interview processes and review them with the participants once
more. Then ask the participants to consider the information the reports
provide and how they might use that information. (Note that they’ll
have to make assumptions about how they might use the information
from the new reports.) Next, ask participants to determine whether
there is information that would be useful or valuable to the organiza-
tion, but that is not currently being received by anyone within the orga-
nization. If they determine that there is indeed some new information
that the organization could use, go through the normal process of iden-
tifying that information and the subjects and characteristics repre-
sented within it. Sketch samples of new reports for the information,
as appropriate, and add the samples to your existing collection of new
reports.
For example, assume that one of the participants has identified a need
for demographic information; she believes that it would help the organi-
zation identify a more specific target market for its product. None of the
existing reports furnishes this information, so you identify exactly what
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162 Chapter 6 Analyzing the Current Database
she needs by working with her to create a sketch of a report that will
present this information. (She might actually sketch more than one re-
port, but this is neither a problem nor a cause for your concern.) You
then use the appropriate techniques to identify and note the subjects
and characteristics represented within the report and add it to your ex-
isting collection of new reports. Later in the design process, you’ll define
the data structures necessary to support the new information.
Repeat this procedure until the participants can no longer identify any
further information that the organization might find useful or valuable.
After you’re reasonably confident that you’ve accounted for all of the or-
ganization’s information requirements, suspend the interview process
and begin the process of compiling the preliminary field list.
It’s important for you to understand that you may have to revisit this
process, even though you and the participants may believe that you’ve
accounted for all the information the organization could possibly use.
You’ll commonly identify new information as the database-design pro-
cess unfolds.
Compiling a Complete List of Fields
The Preliminary Field List
Now that you have completed your analysis of the current database and
the interviews with users and management, you can create a preliminary
field list. This list represents the organization’s fundamental data re-
quirements and constitutes the core set of fields that you’ll define in the
database. You create the preliminary field list using a two-step process.
Step One: Review and Refine the List of Characteristics
The first step involves reviewing and refining the list of characteristics
you compiled throughout the analysis and interview process. As you
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Compiling a Complete List of Fields 163
learned in Chapter 3, a field represents a characteristic of a particular
subject; therefore, each item on your list of characteristics will be-
come a field. Before you transform those characteristics into fields,
however, you first need to review the list to identify and remove dupli-
cate characteristics.
During the interviews, you identified various characteristics within each
participant’s responses, compiling them into a list as the interview pro-
gressed. There were probably times when you mistakenly added the
same characteristic to the list more than once, or unknowingly referred
to the same characteristic by two or more different names. As a result,
your list of characteristics requires some refinement.
Refining Items with the Same Name
Begin refining your list of characteristics by looking for items with the
same name. When you find one or more occurrences of a particular
name, determine whether they all represent the same characteristic.
Remove all but one occurrence of the name from the list if they do rep-
resent the same characteristic; otherwise, determine what each in-
stance of the name represents. You’ll often find that a duplicate name
represents the same type of characteristic as its original counterpart,
but should be associated with a different subject than its counterpart.
In this case, you rename the duplicate to reflect how it relates to the ap-
propriate subject.
Assume, for example, that the item “Name” appears three times on your
list of characteristics. Your first inclination will probably be to remove
two of the occurrences because your current objective is to eliminate
duplicate characteristics. However, you should determine whether each
instance of “Name” represents a distinct characteristic before you re-
move it. You can easily make this determination by examining your in-
terview notes; this will help you remember when and why you added the
item to the list.
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After careful examination, you discover that the first occurrence of
“Name” represents a characteristic of the subject “Clients,” the second, a
characteristic of the subject “Employees,” and the third, a characteristic
of the subject “Contacts.” You resolve this duplication by renaming each
occurrence of “Name” (using the subject as a prefix) to reflect its true
meaning. Now you’ll have three new characteristics called “Client Name,”
“Employee Name,” and “Contact Name.”
Items similar to “Name” commonly appear on a list of characteristics,
and you must address them in the same manner. You’ll commonly see
one or more occurrences of items such as “Address,” “City,” “State,” “Zip
Code,” and “Phone Number,” and you can refer to them collectively as
generic items. The point here is that you must rename each instance of
a generic item to reflect its true relationship to a particular subject,
thus ensuring that you have as accurate a field list as possible.
Refining Items Representing the Same Characteristic
Now look for items that represent the same characteristic and remove
all but one. The idea here is that a given characteristic should appear
only once in the list of characteristics. For example, assume that “Prod-
uct #,” “Product No.,” and “Product Number” appear on your list of
characteristics. It’s evident that these items all represent the same
characteristic, and you need only one of them on your list. Choose the
one that conveys the intended meaning clearly, completely, and unam-
biguously and remove the remaining items from the list of characteris-
tics. (In this case, the best choice is “Product Number” because it fulfills
the previous criteria.)
Ensuring Items Represent Characteristics
Finally, make sure that each item on your list represents a characteristic.
It’s easy to place items accidentally on the list that represents subjects.
You can test each item by asking yourself questions such as these:
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Compiling a Complete List of Fields 165
Can this word be used to describe something?
Does this word represent a component, detail, or piece of some-
thing in particular?
Does this word represent a collection of things?
Does this word represent something that can be broken down
into smaller pieces?
Depending on the item you’re working with, some questions are easier
to answer than others. When you find that an item represents a subject
rather than a characteristic, remove it from the list of characteristics
and add it to the list of subjects. Be sure to identify the new subject’s
characteristics and add them to the existing list of characteristics.
For example, say “Item” appears on your list of characteristics, and
you’re not quite sure whether it represents a characteristic or a subject.
Use the questions above to help you make a determination.
Can “Item” be used to describe something?
Does “Item” represent a component, detail, or piece of something
in particular?
You could make a case that “Item” helps to describe a sale inasmuch as
it identifies what a customer purchased. On the other hand, you could
also say that “Item” isn’t a characteristic because it doesn’t represent a
singular aspect of a sale. “Date Sold,” for example, represents a singular
characteristic of a sale. Leaving the quandary surrounding these ques-
tions unresolved, you go on to the next question.
Does “Item” represent a collection of things?
You can answer this question easily by looking at the plural form of the
word, which in this case is “Items.” If “Items” can be referred to as a
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166 Chapter 6 Analyzing the Current Database
collection, it is a subject. It’s beginning to become clear that “Item”
does represent a collection of some sort, and you can make a final de-
termination by asking yourself the last question:
Does “Items” represent something that can be broken down into
smaller pieces?
You can answer this question by determining whether you can identify
any characteristics for “Items.” If you can, then “Items” definitely rep-
resents a subject and you should move it to the list of subjects. You
also need to identify its characteristics and add them to your list of
characteristics.
Continue with this procedure until you’ve reviewed and refined the en-
tire list of characteristics to your satisfaction. When you are through,
you have your first version of the preliminary field list. Now you’ll add
new items to it and refine it further during the next step.
Step Two: Determine Whether There Are New Characteristics in Any of Your Samples
This step involves an examination of all the samples you gathered
throughout the analysis process. Your goal is to determine whether
there are characteristics on the samples that need to be added to the
preliminary field list.
Begin this step by highlighting every characteristic you find on each
sample. Then, examine each characteristic and determine whether it’s
already on the preliminary field list; cross it out on the sample if it’s al-
ready on the list. Next, study the remaining characteristics and deter-
mine whether any of them has the same meaning as an existing field; if
it does, cross it out on the sample. (Use the same procedure you used in
the first step to make this determination.) Finally, add any highlighted
characteristics remaining on the samples to the preliminary field list.
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Compiling a Complete List of Fields 167
For example, say you’re working with the data-collection sample shown
in Figure 6.14.
Highlight each characteristic you find on the sample, as shown in Fig-
ure 6.15.
You’re likely to find multiple occurrences of various characteristics in
some of the samples. As you can see, both “Name” and “Phone No.” ap-
pear twice on this particular sample. You can cross out the duplicates in
this case because they have the same meaning as the original instances.
To continue with the example, say you reviewed the preliminary field list
and found that every characteristic on the sample is already on the list
with the exception of “Name” and “Phone No.” Cross out the existing
items on the sample to show that you have accounted for them. Before
Mike's Bike Shop
File Edit View Insert Format Records Tools Window Help
Edit< Back Next > Save
Supplier Information
Company:
Address:
City:
State: Zip:
Acme Power Tools
TX 79925
635 Montana Ave
El Paso 598-4455
598-5715
Active
Office Phone:
FAX Number:
Status:
Contacts
Name: George Barlett
Name:
532-9228Phone No.:
Phone No.:
Figure 6.14. An example of a data-collection sample.
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168 Chapter 6 Analyzing the Current Database
you add “Name” and “Phone No.” to the preliminary field list, however,
make sure that the names of these items properly describe their rela-
tionship to the subject represented within the sample. In this case, the
two remaining items represent characteristics of a group of people
known as “Contacts.” Therefore, you rename these characteristics (us-
ing the subject as a prefix) as “Contact Name” and “Contact Phone
Number,” and then add them to the preliminary field list. Repeat this
procedure for each sample you’ve gathered until you’ve gone through all
the samples you’ve collected. When you’re through, you have the second
version of the preliminary field list.
A Side Note: Value Lists
As you examine the characteristics on a database, spreadsheet, or Web
page sample, record on a sheet of paper the name of each characteristic
that incorporates a value list (also known as an enumerated list). This
list specifies the acceptable range of values for a particular characteris-
Mike's Bike Shop
File Edit View Insert Format Records Tools Window Help
Edit< Back Next > Save
Supplier Information
Company:
Address:
City:
State: Zip:
Acme Power Tools
TX 79925
635 Montana Ave
El Paso 598-4455
598-5715
Active
Office Phone:
FAX Number:
Status:
Contacts
Name: George Barlett
Name:
532-9228Phone No.:
Phone No.:
Figure 6.15. A sample with highlighted characteristics
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Compiling a Complete List of Fields 169
tic and often enforces a given business rule. (You’ll learn about business
rules in Chapter 11.) For example, say you work for a manufacturing
company that uses four specific vendors to deliver its goods to custom-
ers across the nation. You could use a value list to ensure that a user
selects one of those four vendors to ship a particular order. Figure 6.16
illustrates this example (note SHIP VIA) and also shows two common
types of value list.
When you record the name of a characteristic that incorporates a value
list, also record the values within the list. If the list contains a large
number of values, write a brief description of the type of values in the
list and (if possible) a minimum and maximum value; otherwise, write
down each of the values. Figure 6.17 shows an example of the record
you’re creating.
Mike's Bike Shop
File Edit View Insert Format Records Tools Window Help
Edit< Back Next > Save
Sales Order Information
Order #:
Order Date:
Ship Date:
Sales Rep:
May 16, 2002
May 20, 2002
Processing
Ship Via:
Status:901225
Airborne DHL FedEx UPSHernandez, Mike
Hernandez, Mike Howard, Ed Hughes, Mark Jamison, Jonah Jordan, Mark
Hernandez, Mike
Figure 6.16. A database screen with two value lists.
A value list can appear as a drop-down list or scrollable list.
A value list can also appear as a set of buttons or check boxes
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170 Chapter 6 Analyzing the Current Database
You can be discerning about the characteristics you choose to record.
For example, it’s unnecessary for you to record characteristics that ac-
cept simple or obvious sets of values, such as “yes/no,” “true/false,” or
“active/inactive.” Instead, you should record characteristics that accept
distinct, specific sets of values.
Set this sheet (or sheets) aside after you’ve finished recording the appro-
priate characteristics. You’ll refer to this sheet when you define field
specifications for the fields in the database and again when you define
business rules.
The Calculated-Field List
There’s one final refinement you must make to the preliminary field
list before you can consider it complete: You must remove every calcu-
lated field and place it on a separate list. This new list becomes your
Characteristics Incorporating a Value List
Characteristic
Sales Rep The name of every employee within the organization whose position is that of a sales rep.
Value List
Ship Via Airborne, DHL, FedEx, UPS
Category Accessories, Bikes, Clothing, Components,
Maintenance, Racks, Wheels
Department Accessories, Bikes, Clothing, Service,
Figure 6.17. Recording characteristics that incorporate value lists.
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Compiling a Complete List of Fields 171
calculated-field list. Recall from Chapter 3 that a calculated field is one
that stores the result of a string concatenation or mathematical expres-
sion as its value. You list calculated fields separately because you’ll use
them in a specific manner later in the design process.
You build the calculated-field list using existing fields from the prelimi-
nary field list. Examine the preliminary field list and determine whether
there are fields that fit the description of a calculated field. Fields that
have names containing words such as “amount,” “total,” “sum,” “aver-
age,” “minimum,” “maximum,” and “count” are likely candidates for the
calculated-field list. Common names for calculated fields include “Sub-
total,” “Average Age,” “Discount Amount,” and “Customer Count.” As
you identify each calculated field, remove it from the preliminary field
list and place it on the calculated-field list. When you’ve completed your
examination of all of the fields in the preliminary field list, you’ll have
two completely new lists: a third version of the preliminary field list and
a calculated-field list.
Reviewing Both Lists with Users and Management
Conduct brief interviews with users and management to review the items
that appear on the preliminary field list and the calculated-field list. Your
objective here is to determine whether there are fields that have been
omitted from either list. You can continue with the next step in the design
process when everyone is satisfied that the lists are complete; otherwise,
identify the fields that are missing and add them to the appropriate list.
Once the interviews are complete, you’ll have a “final” version of each list.
Be sure you conduct these interviews because the participants’ feed-
back provides you with a means of verifying the fields on both lists. Let
me remind you once again to avoid becoming too invested in the idea
that these lists are absolutely complete and final. At this point you still
may not have identified every field that needs to be included in the data-
base—inadvertently, you’re almost sure to miss a few fields—but if you
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172 Chapter 6 Analyzing the Current Database
strive to make your lists as complete as you can, the inevitable addi-
tions or deletions will be quick and easy to make.
You’ve already defined the mission statement and mission objectives for
Mike’s new database. Now it’s time to perform an analysis, conduct in-
terviews, and compile a preliminary field list.
First, analyze Mike’s current database. As you already know, he keeps
most of his data on paper; the only exception is the product inventory
he maintains in a spreadsheet program. Gather samples of the various
papers Mike uses to collect data and a screen shot or printout of the
spreadsheet he uses to maintain the product inventory. Assemble these
samples together in a folder for later use. For example, Figure 6.18
shows a sample of the index cards Mike uses to collect customer infor-
mation, along with a screen shot of his spreadsheet program.
Next, identify the methods Mike uses to present information. He and his
staff currently produce a variety of reports that present the information
they need to conduct their daily affairs. They generate most of the re-
ports using an old typewriter and the rest using a word-processing pro-
gram on the computer. Gather samples of all the reports and place them
in a folder for later use. Figure 6.19 shows a sample report that Mike
creates with his typewriter.
Now you’re ready to interview Mike’s staff. Here are some points to re-
member as you’re conducting the interviews:
1. Identify the types of data staff members are using and how they
use that data. Be sure to use the subject-identification technique
and the characteristic-identification technique to help you ana-
lyze responses and formulate follow-up questions.
CASE STUDY
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Case Study 173
2. Review all the samples you gathered during the beginning of the
analysis process. Determine how each sample is used, write an
appropriate description, and attach the description to the sample.
3. Identify the staff’s information requirements. Determine what
information they’re currently using, what additional information
they need (remember to use the samples), and what kind of infor-
mation they believe they’ll need as the business evolves.
Steven Pundt 363-9755
Apartment 2B
2380 Redbird Lane
Seattle, WA 98115
He’s primarily interested in mountain bike stuff.
Keep him abreast of the summer bike tours.
Mike's Bike Shop - Product Information
File Edit View Insert Format Tools Data Window Help
Product Description
Shur-Lok U-Lock
SpeedRite Cyclecomputer
SteelHead Microshell Helmet
SureStop 133-MB Brakes
Diablo ATM Mountain Bike
UltraVision Helmet Mount Mirrors
SRP
75.00
65.00
36.00
23.50
1,200.00
7.45
Product ID
9001
9002
9003
9004
9005
9006
1 2 3 4 5 6
7
B C D EA Qty On Hand
20
33
16
10
Category
Accessories
Accessories
Components
Bikes
Figure 6.18. A paper-based and a computer-generated sample from Mike’s Bikes.
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174 Chapter 6 Analyzing the Current Database
During the interview, one of the employees wonders whether she can
add a new field to the supplier phone list report. How do you respond?
You hand her the report and ask her to attach a note indicating the
name of the new field and a brief explanation of why she believes it’s
necessary. When she’s finished, return the sample to the report sam-
ples folder. Figure 6.20 shows the report sample with the attached note.
Company Name
ACME Cycle Supplies
B & M Bike Supplies
CycleWorks
Evanstone's Cycle Warehouse
Contact Name
George Chavez
Carol Ortner
Julia Black
Allan Davis
Phone Number
633-9910
527-3817
527-0019
636-9360
Supplier Phone List
Figure 6.19. A report sample from Mike’s Bikes.
Supplier Phone List
Company Name
ACME Cycle Supplies
B & M Bike Supplies
CycleWorks
Evanstone's Cycle Warehouse
Contact Name
George Chavez
Carol Ortner
Julia Black
Allan Davis
Phone Number
633-9910
527-3817
527-0019
636-9360
Can we include fax number?
We can process special
orders more quickly via fax.
Figure 6.20. A report sample with attached note suggesting a new field.
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Case Study 175
You’ll conduct the final interview with Mike. Keep the following points in
mind as you speak with him:
1. Identify the reports he currently receives; you need to know what
kind of information he uses to make business decisions. If he
receives reports that are not represented in your group of report
samples, obtain a sample of each report and add it to the group,
updating the subject and characteristic lists as needed.
2. Review the group of report samples with him and determine
whether he can identify subjects or characteristics that have been
overlooked by his staff. Use the appropriate techniques to identify
these items and then add them to the appropriate list.
3. Determine whether there is any additional information Mike needs
to supplement the information he currently receives.
4. Determine what types of information Mike will need as the busi-
ness evolves.
As you and Mike discuss his future information needs, he indicates that
there is some new information he’d like to receive once the business re-
ally gets rolling: He’d like to see total bike sales by manufacturer. He be-
lieves this information would help him determine which bikes should
be consistently well stocked. Such a report does not currently exist,
so have Mike sketch it out on a sheet of paper. Next, identify the sub-
jects and characteristics represented within the report and add them
to the appropriate list. Then add the new report to your group of re-
port samples. Figure 6.21 shows the sketch of Mike’s new report.
Your analysis is now complete. You’ve interviewed Mike and his staff,
you’ve gathered all the relevant samples, and you’ve created a list of
subjects and a list of characteristics. A partial list of subjects and char-
acteristics is shown in Figure 6.22. All you need to do now is to create
your preliminary field list.
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176 Chapter 6 Analyzing the Current Database
As you already know, you need to refine the list of characteristics before
it can become the first version of the preliminary field list. Remove all
duplicate characteristics, delete items that represent the same charac-
teristic, and refine those items that have generic names. (Remember the
problem with the characteristic called “Name”? If you find such charac-
teristics, now is the time to resolve them.) Next, review all your samples
Bike Sales Summary
Company Name
Altair Bicycles
Bandido Bikes
Bike Model
ATB 600-A
Cruiser 500
Baja Delight
Diablo Rojo
Total Units Sold
12
7
16
9
Figure 6.21. The sketch of Mike’s new report.
List of Characteristics as of 06/15/02
Address Home Phone
Birth Date Last Name
Category Name
City Phone
Comments Product No.
First Name State
List of Subjects as of 06/15/02
Customers Sales
Employees Suppliers
Products
Figure 6.22. Partial lists of subjects and characteristics for Mike’s Bikes.
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Summary 177
and determine whether they contain characteristics that do not cur-
rently appear on the preliminary field list. Add to the list any new char-
acteristics that you find. When you complete these tasks, you have the
first version of your preliminary field list.
Now you remove all the calculated fields from the preliminary field list
and place them on their own list; this becomes your new calculated-field
list. Figure 6.23 shows a small portion of your final preliminary field list
and calculated-field list.
Summary
This chapter begins by discussing why you should analyze the organiza-
tion’s current database. You learned that the analysis helps you identify
❖ Note You may have noticed that each list includes a date in the title. It’s a good idea to date your lists so that you can main-
tain a clear history of their development.
Preliminary Field List as of 07/05/02
Office PhoneBirth Date
Unit PriceEmployee City
CategoryEmployee Address
Product NameEmployee Name
Invoice NumberCustomer Name
Invoice DateCustomer Address
Calculated Field List as of 07/05/02
Discount Amount
Grand Total
Item Total
Subtotal
Figure 6.23. A partial preliminary field list and a calculated-field list.
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178 Chapter 6 Analyzing the Current Database
aspects of the current database that will be useful to you when you de-
sign the new database. Armed with this information, you can design a
database that best suits the organization’s needs. Next, we briefly
looked at the two types of databases organizations commonly used:
paper-based databases and legacy databases. We ended this discussion
by identifying the three steps used in the analysis process: reviewing the
way data is collected, reviewing the way information is presented, and
conducting interviews with the organization’s staff.
The chapter continues with a discussion of the review process. You
learned how to review the ways the organization collects its data and
how to assemble a set of data-collection samples. Then you learned how
to review the ways the organization presents information and how to as-
semble a set of report samples.
Next, we discussed the process you use to conduct interviews, and you
learned why interviews are useful at this stage of the design process.
During this discussion you learned two techniques that are crucial to
the success of interviews: the subject-identification technique and the
characteristic-identification technique.
Conducting user interviews was the next subject of discussion. We ex-
amined the four issues you must address during these interviews, along
with the techniques you use to address them. Next, we discussed con-
ducting management interviews. Here you learned about the issues and
techniques these interviews incorporate.
Finally, we discussed the process of compiling a list of fields based on
the list of characteristics and the characteristics that appear in the
samples. You learned that you decompose the field list into two separate
lists: a preliminary field list and a calculated-field list. The preliminary
field list enumerates the organization’s fundamental data requirements
and establishes the core set of fields you must define in the database.
The calculated-field list consists of fields that contain values resulting
from string concatenations or mathematical expressions.
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Review Questions 179
Review Questions
1. State two goals of analyzing the current database.
2. True or False: You can adopt the current database structure as
the basis for the new structure.
3. What is a legacy database?
4. State two steps of the analysis process.
5. Which types of computer software programs should you review
during the analysis?
6. Why should you conduct interviews after you gather data-collection
and information-presentation samples?
7. How do you use “open” and “closed” questions?
8. What is the subject-identification technique?
9. How do you identify specific attributes for a particular subject?
10. True or False: You should interview users and management at the
same time.
11. What three basic types of information requirements must you
identify?
12. What is the preliminary field list?
13. State why each item on this list should have a unique name.
14. What is a value list?
15. What are calculated fields? What (if anything) should you do
about them?
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181
7 Establishing Table Structures
It is a capital mistake to theorize before one has data. —SHERLOCK HOLMES,
THE ADVENTURES OF SHERLOCK HOLMES
Topics Covered in This Chapter
Defining the Preliminary Table List
Defining the Final Table List
Associating Fields with Each Table
Refining the Fields
Refining the Table Structures
Case Study
Summary
Review Questions
Organizations use databases to keep track of various subjects that are
important to them. For example, a medical clinic keeps track of, among
other things, its patients, doctors, and appointments; an equipment-
rental business must maintain data on its customers, equipment, and
rental agreements; and a registrar’s office is concerned (at the very
least) with students, teaching staff, and courses. In every case—and in
any other scenario you can imagine—a table within the database repre-
sents each subject. Furthermore, each table is composed of fields,
which represent the characteristics that define or describe the subject
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182 Chapter 7 Establishing Table Structures
of the table. Tables constitute the very foundation of the database, and
they guarantee a solid and sound foundation when they are properly
designed.
Defining the Preliminary Table List
During this portion of the database-design process, you’ll define a pre-
liminary table list that you’ll use to identify and establish the tables for
the new database. You’ll use three procedures to develop this list. The
first involves using the preliminary field list, the second involves using
the list of subjects you gathered during the interviewing process, and
the third involves using the mission objectives you defined at the begin-
ning of the database-design process. You’ll then move on to build the
structure of each table using fields from the preliminary field list.
Identifying Implied Subjects
The process of defining the tables for the database begins with a review
of the preliminary field list. Your objective is to identify subjects that are
implied by the fields on the list.
You may wonder why you’re reviewing the preliminary field list instead
of starting with the list of subjects. The list of subjects does seem to be a
more intuitive place to start. After all, you’ve carefully built this list dur-
ing the interview process, and you’ve been influenced by the conversa-
tions you’ve had with the users and management. Surely, all of this has
helped you identify every subject that needs to be represented in the da-
tabase. You may be correct, but you could have a minor problem if
you’re wrong: missing tables.
Studying the fields on the primary field list helps you identify subjects
from an unbiased viewpoint—you’re letting the fields “talk” to you. It’s
crucial that you now look at this list as objectively as possible—as
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Defining the Preliminary Table List 183
though you’ve never seen it before—without any of the biases you’ve as-
similated during the interview process. This enables you to see how cer-
tain groups of fields suggest specific subjects, some of which may not
have been identified during the interview process. You can also use the
preliminary field list to verify many of the subjects on the list of sub-
jects. Using the preliminary field list in these ways allows you to cross-
check your previous work and helps you ensure that the new database
structure includes all of the necessary subjects.
As you review the preliminary field list, ask yourself whether a certain
set of fields defines or describes a particular subject. Move on to an-
other set of fields if nothing readily comes to mind. When you can infer
a subject from the field in the list, enter that subject on a new prelimi-
nary table list. Figure 7.1 shows a partial sample of a preliminary field
list and illustrates how a subject can be suggested by a set of fields.
Figure 7.1. Using the preliminary field list to identify subjects.
Preliminary Field List
Phone Extension
Status
Student First Name
Student Last Name
Home Phone
Address
City
State
Course Code
Course Name
Course Description
Lab Fee
Faculty First Name
Faculty Last Name
Date Hired
Phone Extension
These fields
suggest
“Courses.”
These fields
suggest
“Faculty.”
These fields
suggest
“Students.”
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184 Chapter 7 Establishing Table Structures
Continue your review until you’ve scanned all the fields and identified
as many subjects as possible. Be sure to add each subject you identify
to the preliminary table list. This list will grow as you work with the list
of subjects and mission objectives. Figure 7.2 shows an example of the
first version of a preliminary table list.
Using the List of Subjects
Now, create a second version of the preliminary table list by merging the
list of subjects (created during the interviews with users and manage-
ment) with the first version of the preliminary table list (compiled by
studying the preliminary field list). This new version contains a more com-
plete list of tables. Merging the two lists is a three-step process, which in-
volves resolving duplicate items, resolving items that represent the same
subject, and combining the remaining items together into one list.
Step One: Resolve Duplicate Items
Start this step by reviewing and crosschecking each item on the list of
subjects against the items on the preliminary table list. Your objective
here is to identify duplicate items, which are items on the list of subjects
Figure 7.2. The first version of the preliminary table list.
Preliminary Table List
Courses
Faculty
Labs
Students
Classrooms
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Defining the Preliminary Table List 185
that already appear on the preliminary table list. You must be very care-
ful how you resolve the duplicate items that you find. Begin by deter-
mining whether the items represent different subjects, despite the fact
that they share the same name. (Use your interview notes as necessary
to help you make the determination.) If they do represent different sub-
jects, rename each item so that it accurately identifies the subject it
represents and then add both items to the preliminary table list; other-
wise, determine whether they truly represent the same subject. When
you determine that both items do represent the same subject, cross out
the item on the list of subjects and keep the one that appears on the
preliminary table list. Then resume the review until you’ve examined all
of the items on both the list of subjects and the preliminary table list.
Let’s take a look at an example of this process.
Assume that you’re developing a database for an equipment rental busi-
ness, and you’re working with the list of subjects and the preliminary
table list shown in Figure 7.3.
As you review these lists, you discover two duplicate items: “Equipment”
and “Rental Agreements.” These items warrant further examination, so
Figure 7.3. The list of subjects and the preliminary table list for an equipment rental business.
Preliminary Table ListList of Subjects
Clients
Equipment
Rental Agreements
Services
Employees
Customers
Rental Agreements
Sales Reps
Equipment
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186 Chapter 7 Establishing Table Structures
you start with “Equipment” and try to determine whether each occur-
rence represents a different subject. In reviewing your interview notes,
you find that “Equipment” on the list of subjects represents items such
as tools, appliances, and audiovisual equipment. Then you remember
that “Equipment” on the preliminary table list also includes trucks,
vans, and trailers. You review your interview notes further and discover
that vehicle rentals are treated differently from “regular” equipment
rentals. Therefore, each occurrence of “Equipment” does represent a
different subject. You resolve the duplication by keeping one occurrence
of “Equipment” and renaming the other “Vehicles.” You then list both
items on the preliminary table list.
Now you go through the same process with “Rental Agreements.” For-
tunately, you discover that both occurrences share exactly the same
meaning. The only thing you have to do in this case is cross out
“Rental Agreements” on the list of subjects. Now you can continue
your review until you’ve inspected each item on the list of subjects.
Figure 7.4 shows the revised list of subjects and the preliminary
table list.
Figure 7.4. The revised list of subjects and the revised preliminary table list (first view).
Preliminary Table ListList of Subjects
Clients
Equipment
Rental Agreements
Services
Employees
Customers
Rental Agreements
Sales Reps
Equipment
Vehicles
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Defining the Preliminary Table List 187
Step Two: Resolve Items That Represent the Same Subject
Your objective during this step of the merge process is to determine
whether an item on the list of subjects and an item on the preliminary
table list represent the same subject even though they have different
names. When you identify such a set of items, select the name that best
represents the subject and use it as the sole identifier for that subject.
Then deal with the name in this manner:
• If the name you’ve selected already appears on the preliminary ta-
ble list, cross out its counterpart on the list of subjects.
• If the name appears on the list of subjects, remove its counterpart
on the preliminary table list and replace it with the name from the
list of subjects.
Repeat this process until you’ve covered all the items on the list of
subjects.
Continuing with the equipment rental business example, assume you’ve
discovered that “Clients” and “Employees” on the list of subjects and
“Customers” and “Sales Reps” on the preliminary table list represent
(respectively) the same subject (see Figure 7.4). Deciding to deal with
“Clients” and “Customers” first, you review your interview notes and de-
termine that “Customers” is the name that best represents both the
people and the organizations that rent equipment from the business.
You then resolve the duplication by keeping “Customers” and crossing
out “Clients.” Moving on to the next set of duplicate items, you decide to
keep “Employees” and discard “Sales Reps” because you believe that
“Employees” best describes those people who are employed by the busi-
ness, regardless of their position. Figure 7.5 shows a revised version of
both lists and the resolution of the duplicate items.
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Step Three: Combine the Items on the List of Subjects and the Preliminary Field List
The final step of this process is the easiest of the three. All you do is add
the remaining items from the list of subjects to the preliminary table
list. Then throw away the list of subjects—you won’t need it anymore.
The list that remains becomes the second version of the preliminary ta-
ble list. That’s all there is to it! Figure 7.6 shows the second version of
Figure 7.5. The revised list of subjects and the revised preliminary table list (second view).
Preliminary Table ListList of Subjects
Clients
Equipment
Rental Agreements
Services
Employees
Customers
Rental Agreements
Vehicles
Equipment
Employees
Figure 7.6. The second version of the preliminary table list.
Preliminary Table List
Customers
Rental Agreements
Employees
Equipment
Services
Vehicles
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Defining the Preliminary Table List 189
the preliminary table list, which is the result of merging the two lists
shown in Figure 7.5.
Using the Mission Objectives
In this third and final procedure, you use the mission objectives to de-
termine whether you’ve overlooked any subjects during the previous
two procedures. This is your final opportunity to add tables to the pre-
liminary table list.
Start with the first mission objective, and use the subject-identification
technique to identify the subjects represented in that statement. Under-
line each subject you identify and then crosscheck it against the items
on the preliminary table list. Use the same techniques here that you
used in the previous procedure.
1. When an item you underlined in a mission objective statement
matches an item on the preliminary table list, determine whether
the items represent different subjects. If they do, assign an appro-
priate name to each occurrence and then add each one to the
preliminary table list; otherwise, cross out the duplicate item on
the mission objective.
2. When an item you underlined in the mission objective statement
has a name that is synonymous with the name of an item on the
preliminary table list and both items represent the same subject,
select the name that best identifies that subject and use it in the
preliminary table list.
3. When an item you underlined in the mission objective statement
represents a new subject, add it to the preliminary table list.
Repeat these steps until you’ve worked through all the mission objec-
tives. Here’s an example of how you use these techniques to review the
mission objectives.
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Assume that you’re designing a database for a flight training school.
You’re just starting this particular process, and you’ve just used the
subject-identification technique on the following statement:
We need to maintain data on our pilots and their certifications.
You now crosscheck the subjects you identified in this mission objective
against the items in the preliminary table list shown in Figure 7.7.
In this case, you cross out “pilots” in the mission objective statement
because it already exists on the preliminary table list and it represents
the same subject. You then decide to examine “certifications” further,
and, after some careful thought, you make these observations:
1. It does not appear on the preliminary table list.
2. It doesn’t duplicate any item on the preliminary table list.
Figure 7.7. The preliminary table list for a flight training school.
Preliminary Table List
Courses
Employees
Maintenance History
Pilots
Planes
Students
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Defining the Final Table List 191
3. Its name is not synonymous with any item on the preliminary table
list.
4. It doesn’t represent the same subject as any other item on the
preliminary table list.
These findings indicate that “certifications” is a new item and should be
added to the preliminary table list. So, you add it to the preliminary ta-
ble list and cross it out on the mission objective statement; this shows
you that you’ve already dealt with this particular item. Figure 7.8 shows
the revised version of the preliminary table list.
Defining the Final Table List
Your preliminary table list is as complete as it can be at this point, so
you’ll now transform it into a final table list. This new list incorporates two
elements that are not currently on the preliminary table list: table type
and table description. Figure 7.9 shows an example of a final table list.
Figure 7.8. The revised preliminary table list.
Preliminary Table List
Courses
Employees
Maintenance History
Pilots
Planes
Students
Certifications
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A table type allows you to classify a table by the role it plays within the
database and provides you with a means of identifying tables that func-
tion in a similar manner. The table’s role determines its type, and there
are four table types that you can associate with a given table:
1. A data table represents a subject that is important to the organiza-
tion and is the primary foundation of the information that the
database provides. (You’ll learn more about data tables later in this
chapter.)
2. A linking table establishes a link between two tables in a many-
to-many relationship. (Chapter 10 covers linking tables in more
detail.)
Figure 7.9. An example of a final table list.
Final Table List
Courses
Classrooms
Name
Data
Data
Type
The spaces or areas within a facility reserved for the purpose of conducting class proceedings. Information regarding the physical aspects, on-site resources, and availability of these areas is useful because it allows us to assign classes to the facility that can make the best use of these areas.
Description
The programs of instruction conducted through courses offered by this institution. Course information must always reflect the addtion of new courses, the deletion of old courses, and the continuing evolution of existing courses.
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Defining the Final Table List 193
3. A subset table contains fields that are related to a particular data
table and further describes the data table’s subject in a very spe-
cific manner. (You’ll learn more about subset tables later in this
chapter.)
4. A validation table contains relatively static data and is a crucial
component of data integrity. (Chapter 11 provides further details
on this type of table.)
A table description provides a clear definition of the subject represented
by the table and states why the subject is important to the organization.
There are certain guidelines that govern how you create a table descrip-
tion, and you’ll learn about them later in this chapter. There is a final
task you have to perform before you transform your preliminary table
list into the final table list: refining the table names.
Refining the Table Names
Naming a table is a more complex affair than you may realize at the mo-
ment. As you learned in Chapter 3, a table represents a single subject;
therefore, its name must clearly identify the subject it represents. The
following guidelines will help you create table names that are clear, un-
ambiguous, descriptive, and meaningful. They will also help ensure that
you name your tables in a consistent manner.
Guidelines for Creating Table Names
• Create a unique, descriptive name that is meaningful to the entire
organization. Using unique names helps to ensure that each table
clearly represents a different subject and that everyone in the or-
ganization will understand what the table represents. (If you en-
counter duplicate table names at this point, resolve the problem
using the techniques you learned earlier in this chapter.) Choose
names that are descriptive enough to be self-explanatory. “Vehicle
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Maintenance” is an example of a good, descriptive name. Defining
a unique and descriptive name does take some work on your part,
but it’s well worth the effort in the long run.
• Create a name that accurately, clearly, and unambiguously identi-
fies the subject of the table. Vague or ambiguous names usually
indicate that the table represents more than one subject. When
you encounter such a name, identify the subjects the table truly
represents and then treat each subject as a separate table.
“Dates” is a good example of a vague table name. You really don’t
know what the table represents without referring to its descrip-
tion. For example, assume you’re designing a database for an en-
tertainment agency and this table appears in the preliminary
table list. Upon seeing this table name, you decide to review your
interview notes. You discover that one person says “Dates” repre-
sents appointments for client meetings, and another person says
it represents booking dates for the agency’s stable of entertainers.
This table clearly represents two subjects, so you remove “Dates”
from the preliminary table list and replace it with two new tables
called “Client Meetings” and “Entertainer Schedules.”
Possibly the most vague and ambiguous name you could assign to
a table is “Miscellaneous”—it doesn’t identify a single subject
whatsoever. You might occasionally feel compelled to create a
“Miscellaneous” table because you just can’t figure out what to do
with certain fields on your preliminary field list. When that hap-
pens, stop, take a break, and then come back and re-examine
those fields. Carefully and methodically apply the design tech-
niques you’ve learned, and you’re sure to determine what to do
with the fields after all.
• Use the minimum number of words necessary to convey the subject
of the table. Everyone in the organization should be able to iden-
tify what the table represents without having to read its descrip-
tion. Although your objective is to create a short, succinct table
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Defining the Final Table List 195
name, avoid using a minimalist approach. “TD_1” is a good exam-
ple of a name that is exceedingly short. You won’t have the slight-
est idea what this table represents unless you know the meaning
of each character in the name. You should also avoid going in the
opposite direction as well. “Multiuse Vehicle Maintenance Equip-
ment” is much too long and can easily be shortened to just
“Equipment.”
• Do not use words that convey physical characteristics. Avoid using
words such as “file,” “record,” and “table” in the table name be-
cause they add a level of confusion that you don’t need. A table
name that includes this type of word is very likely to represent
more than one subject. Consider the name “Patient Record.” On
the surface, this may appear to be an acceptable name. You’ll re-
alize, however, that there are potential problems with this name
when you take some time to think about what a “patient record”
is supposed to represent. The name contains a word that you’re
trying hard to avoid (“record”) and it potentially represents three
subjects: “patients,” “doctors,” and “examinations.” With this in
mind, remove “patients” from the preliminary table list and re-
place it with three new tables, one for each of the three subjects.
• Do not use acronyms and abbreviations. Acronyms are hard to de-
cipher, abbreviations rarely convey the subject of the table, and
both violate the first guideline in this list. Take acronyms, for ex-
ample. Say you’re helping an organization revise its database
structure and you encounter a table named “SC.” How do you
know what the table represents without knowing the meaning of
the letters themselves? The fact is that you can’t easily identify
the subject of the table. What’s more, you may find that the table
means different things to different departments in the organiza-
tion. So, you decide to conduct a brief interview with some of the
staff in order to determine what the letters represent. (Now, this is
the scary part.) To your disbelief, you discover that the folks in
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personnel think it stands for “Steering Committees”; the informa-
tion systems staff believes it to be “System Configurations”; and
the people in security insist that it represents “Security Codes.”
This example clearly illustrates why you should make every effort
to avoid using abbreviations and acronyms in a table name.
• Do not use proper names or other words that will unduly restrict
the data that can be entered into the table. This guideline will keep
you from falling into the trap of creating duplicate table struc-
tures. A name such as “Southwest Region Employees,” for exam-
ple, severely restricts the data that you can enter into this table.
As the organization grows, how will you deal with employees from
other regions? When the organization begins to hire employees in
Washington, Oregon, and Idaho, you’ll have to create a “Pacific
Northwest Region Employees” table, and you’ll have to create a
“Western Region Employees” table when the organization begins
to hire folks in Arizona, Utah, Nevada, and California.
Proper database-design principles dictate that you should not
create duplicate structures such as these because they can be
quite problematic.
1. Users could have a difficult time retrieving data from all three
tables simultaneously.
2. The person maintaining the database would have the added
responsibility of ensuring that the tables are always structur-
ally synchronized. If he adds, modifies, or deletes a field in one
table, he must take the same action on all the other tables.
3. The person maintaining the database would also have the
added responsibility of ensuring synchronized data integrity
between the tables. He must be able to guarantee that data is
completely and accurately transferred from one table to the
other when an employee relocates from one region to another.
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• Do not use a name that implicitly or explicitly identifies more than
one subject. This is one of the most common mistakes you can
make with a table name, and it is relatively easy to identify. This
type of name typically contains the words “and” or “or” and char-
acters such as the slash (\) or ampersand (&); examples include
“Department or Branch” and “Facility\Building.” A table with an
ambiguous name suggests that you may have not identified the
subject clearly or accurately during the analysis and interview
processes. You can rectify this problem by reviewing your notes
and conducting further analysis and interviews as necessary.
Just remember that you must always ensure that each table rep-
resents only one subject.
Another name that falls under this category is “Miscellaneous.”
(Yes, here’s that name again!) A moment ago, I said that this
name didn’t identify a single subject whatsoever; this is a correct
and valid assertion. It is also true, however, that the name im-
plicitly identifies more than one subject; you can’t specifically
identify the subjects because the name is vague and ambiguous.
The Concise Oxford Dictionary, Ninth Edition, defines the word it-
self as follows:
Miscellaneous adj. 1. of mixed composition or character. 2. of various kinds.
You can clearly see the problems that this name creates, so you
should not use it as a table name at all. There are certainly good
reasons not to do so.
• Do use the plural form of the name. As you know, a table repre-
sents a single subject, which can be an object or event. You can
take this definition one step further and state that a table repre-
sents a collection of similar objects or events. For example, a sales
representative wants to maintain data on all of his customers, not
just a single one; and a car rental business wants to keep track of
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all its vehicles, not just the blue BMW. Using the plural form of
the table name is a sound idea because it makes clear your inten-
tion to refer to a collection. Collections, of course, always take the
plural (“Boats,” not “Boat”). In contrast, words that identify fields
are always singular (“Home Phone,” not “Home Phones”). Follow-
ing this rule will make it easy for you to differentiate between ta-
ble names and field names in any documentation you create for
the database. (As you rename your tables, remember that the plu-
ral form of some words does not end in s or es. For instance, the
singular and plural forms of “equipment” are exactly the same.)
Use these guidelines to refine each table name on the preliminary table
list. When you’re finished, this list becomes your final table list and re-
mains so for the duration of the database-design process. Note that the
list is “final” only in the sense that you’ve accounted for all the tables
that you identified throughout the entire analysis process. It’s very likely
that you’ll add new tables to this list based on requirements imposed by
relationships, data integrity, or other information that you develop.
Indicating the Table Types
As you learned earlier in this chapter, you indicate each table’s type on
the final table list. Recall that the four classifications you can use to
identify the table type are data, linking, subset, and validation.
When you first create your final table list, every item on the list is a data
table because it represents a subject that is important to the organiza-
tion and serves as the primary foundation of the information that the
database provides. There will be no linking tables or validation tables on
the list because you have not yet defined relationships or imposed data
integrity. (You’ll address these issues later in the design process.) The
list will not contain subset tables because you define them after you as-
sign fields to the data tables.
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Defining the Final Table List 199
For the moment, designate each table on the final table list as a data ta-
ble. You’ll assign other table types later as the database-design process
continues to unfold.
Composing the Table Descriptions
The table description is another aspect of a table that you record on the
final table list. A table description is crucial because it helps everyone
understand why a given table exists and why the organization is con-
cerned with collecting the data for that table. In fact, the description
must explicitly define the table and state its importance to the organiza-
tion. It doesn’t matter whether the definition comes first or you use
more than one sentence to convey this information—both the definition
and the explanation of the table’s importance must be in the descrip-
tion. The table description also provides a means of validating the need
for a table—if you are unable to explain why a table is important to the
organization, then you need to determine when and how the table was
identified and whether it really is necessary at all.
Just as you had guidelines to help define table names, you also have a
set of guidelines to help you compose a table description that is focused,
concise, unambiguous, and clear.
Guidelines for Composing a Table Description
• Include a statement that accurately defines the table. Anyone
should easily be able to determine the identity of the table from its
description without any confusion or ambiguity. Here’s an exam-
ple of a poor definition for a table named “Suppliers” in a bakery
database. As you can see, it’s not very accurate.
Suppliers—the companies that supply us with ingredients
and equipment
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What if the bakery receives some of its ingredients from local
farmers? The farmers certainly don’t qualify as “companies.”
What type of equipment do these suppliers supply? Cooking uten-
sils? Hand trucks? Delivery racks? Here’s a much better defini-
tion of suppliers.
Suppliers—the people and organizations from whom we
purchase ingredients and equipment
This statement can be used in the table description as the table
definition.
• Include a statement that explains why this table is important to the
organization. A table contains data that is collected, maintained,
manipulated, and retrieved by the organization for a particular
reason. Your statement should explain why the data is important
to the organization. Keeping in mind that this statement becomes
part of your table description, you might be tempted to construct
a statement such as this:
We need the Suppliers table to keep track of the names,
addresses, phone numbers, and contact names of all our
suppliers.
This statement is inadequate because it emphasizes only what
needs to be stored in the Suppliers table instead of amplifying
why the data is important to the business. The next example con-
veys a better sense of why the information is important.
Supplier information is vital to the bakery because it al-
lows us to maintain a constant supply of ingredients and
ensure that our equipment is always in working order.
This is a more effective statement because it conveys the impor-
tance of the data by identifying the services the suppliers provide
to the bakery. It also implies that the bakery could run out of in-
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Defining the Final Table List 201
gredients or have a hard time keeping its equipment in top shape
without the suppliers’ services. This statement now reflects why
the table is important to the organization.
• Compose a description that is clear and succinct. Avoid the com-
mon mistake of restating or rephrasing the table name in your ta-
ble description, as in this example:
Student Schedule—the class schedule of the student
Don’t be too brief or too verbose. You want to make sure that ev-
eryone can identify the table and understand its importance to
the organization, but you also want to avoid furnishing too much
information. Here’s an example of a description that is quite
lengthy and provides more information than is necessary:
Student Schedule—All the classes that a student will at-
tend (including the days, times, and the faculty conduct-
ing the class) during the course of the school year. The
data in this table is important because it will let the stu-
dent know the name of the class and when and where he’s
supposed to be. Also the student will know the duration of
the class, as well as the name of the teacher who is teach-
ing the class.
This can be recast more clearly and succinctly as follows:
Student Schedule—Those classes that the student is
scheduled to attend during this school year. The informa-
tion provided by this table helps the student implement ef-
fective time management and enables the school to figure
class loads and student loads.
The first sentence in this example provides the definition of the
table, and the second sentence states why the table is important
to the academic organization.
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• Do not include implementation-specific information in your table de-
scription, such as how or where the table is used. Avoid state-
ments that indicate how you will specifically use this table, or
how you will physically access it. This type of information is ger-
mane to the database implementation process, which is wholly
separate from the database-design process you’re learning in this
book. Here is an example of a description containing this type of
inappropriate information:
Student Schedule—Those classes that the student is
scheduled to attend during this school year. This informa-
tion is used by the registrar and is accessed from the Stu-
dent Admissions menu in the Registration Program.
• Do not make the table description for one table dependent upon the
table description of another table. Each table description should
be self-explanatory and independent from every other table de-
scription; it should be absolutely unnecessary for you to cross-
reference one table description against another. This is the type of
statement you’re trying to avoid:
Dependents—the spouse, children, or wards of a given
employee. (See description of Employee table for further
information.)
Here’s a much better description:
Dependents—the spouse, children, or wards of a given em-
ployee. This information allows us to make the appropriate
tax deductions for the employee, and is necessary for the
benefits programs in which the employee is enrolled.
• Do not use examples in a table description. An example is a valu-
able communication tool that helps you convey a particular
meaning or concept and is very effective when you use it wisely.
But an example depends on supplemental information (and, in
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Defining the Final Table List 203
some cases, further examples) to complete the idea it’s supposed
to convey. For instance, just think of the number of examples you
would have to use in order to define fully what a table represents.
A well-defined description is clear, succinct, and self-explanatory;
therefore, it does not require an example to convey its meaning.
Interviewing Users and Management
Now you’ll define table descriptions for the tables on the final table list.
You’ll conduct interviews with both users and management, and enlist
their aid in establishing each table’s definition and importance to the
organization. (This is one of the few times that you’ll actually interview
both groups together.) Your main objective is to get a consensus on gen-
eral descriptions for the tables. When your interviews are complete, take
your notes and compose final table descriptions, making sure to follow
the guidelines outlined above. Then confer with both parties once more
to make certain that the descriptions are acceptable and easily under-
stood by all. The final table list is complete when everyone has agreed
on the descriptions.
Consider this example: Assume you’re developing a database for a local
software training organization. Your assistant, John, is conducting an in-
terview with some of the people from the organization. Specifically, he’s
speaking to Mark from the administration department; Frits, the instruc-
tor coordinator; Sara, the vice president of sales; and Caroline, the head
of the organization. The dialogue on the next page is a partial transcript
of John’s interview. John is currently discussing the Students table.
❖Note Unlike the interviews you conducted during the analysis and requirements review stages of the design process, you no longer
need to involve everyone in the organization. But you will work with
a representative group of users and management for the interviews
you’ll conduct throughout the remainder of the design process.
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JOHN: “Okay, let’s talk about the Students table. How
would you describe a ‘student’?”
FRITS: “A student is a private individual who comes in for one of
our classes.”
SARA: “That’s only partially true. A student can also be an indi-
vidual that an organization sends to our classes. For ex-
ample, many of our students come from local banks and
insurance companies, and those organizations pay for
the students’ tuitions.”
MARK: “Yes, you’re quite right. I guess we can simply say that a
student is an individual who comes in for one of our
classes.”
(John makes a note of what Mark just said.)
JOHN: “Good—got it. Does everyone agree with Mark?”
(Everyone nods in approval.)
“Great. Now, how would you explain to someone why stu-
dent information is important to this organization?”
CAROLINE: “Without students, we don’t have a business!”
FRITS: “If we can keep track of the students who attend our
classes, we can send them information regarding our
new classes.”
SARA: “Keeping track of this information allows us to keep bill-
ing and contact information current. This is especially
true for organizations that send their employees to our
classes. Training coordinators move on to other posi-
tions, and we have to know the name of the new person
we’ll be dealing with.”
JOHN: “Good point. Does anyone have anything further to add?
No? Okay, does everyone agree with what has been said
so far?”
(Everyone once again nods in approval. Because no additional com-
ments are made, John jots down some final notes and moves on to
the next table.)
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Associating Fields with Each Table 205
As you can see, conducting this type of interview is a fairly straightfor-
ward affair. Notice how John attempts to get a consensus as he recog-
nizes that no one has anything else to say about the topic at hand. He
then makes note of the points that will help him compose the descrip-
tion and moves on to his next topic.
After John has finished conducting the interview, he uses his notes to
develop a table description for each table on the final table list. He’ll
have to interpret and study the participant’s responses in order to de-
velop a suitable table description. Based on his examination, John
writes the following description:
Students—those individuals who attend our classes. The infor-
mation provided by the data in the Students table allows our
organization to further promote our classes and supports proper
communications with the students.
John then writes a description for each table on the final table list.
When he’s finished, he’ll speak with Mark, Frits, Sara, and Caroline
once more to make sure the descriptions are acceptable and that every-
one understands them without any difficulty.
Associating Fields with Each Table
In Chapter 3 you learned that tables are composed of fields. During this
stage of the database-design process, you’ll assign fields to each table
on the final table list using fields from your preliminary field list.
Assigning fields to a table is a relatively easy process: Determine
which fields best represent characteristics of the table’s subject and
assign them to that table. Repeat this procedure for every table on the
final table list. If you think you can use a field or set of fields to repre-
sent characteristics of more than one table, then assign them accord-
ingly. You’ll discover whether you’ve assigned the appropriate fields to
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206 Chapter 7 Establishing Table Structures
each table later when you go through the process of refining the table
structures.
Begin this process by taking a sheet of legal paper and laying it in
front of you lengthwise from left to right. Write the name of each ta-
ble (from the final table list) across the top of the paper, starting at
the left-hand side; leave enough space between the table names to
give you enough room to list lengthy field names underneath them.
Repeat this procedure, using as many sheets as you need to account
for every table on the list. Continuing with the school database exam-
ple, Figure 7.10 shows the set of table structures currently under
development.
Next, assign fields from the preliminary field list to each table. Deter-
mine which fields best describe or define a table’s subject and then list
these fields underneath the table name. After you’ve assigned all of the
fields you believe to be appropriate for the table, move on to the next
table and repeat the process. Continue in this manner until you’ve as-
signed fields to all the tables. Figure 7.11 shows a partial set of table
structures.
❖ Note In the following examples, you’ll note that I ask you to use sheets of paper for specific procedures. Using paper helps you
avoid the temptation of using an RDBMS program to design your
database. I cannot overemphasize or overstate the fact that you
should not use the computer at all until the database-design pro-
cess is complete unless you’re using some type of database-
design-specific software, such as Computer-Assisted Software
Engineering (CASE) software. By heeding this advice, you will
avoid the traps I discuss later in Chapter 14.
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Associating Fields with Each Table 207
Figure 7.10. Setting up a sheet for listing table structures.
Table Structures
Courses Subjects Instructors Students
Figure 7.11. Listing tables with their associated fields.
Table Structures
Subjects
Subject Name
Subject Description
Category
Credits
Classes
Class Number
Class Name
Room Number
Instructor Name
Subject Name
Students
Student Name
Student Address
Student Phone
Student SSN
Instructor Name
Instructor Address
Instructor Phone
Instructor SSN
Date Hired
Pay Rate
Instructors
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208 Chapter 7 Establishing Table Structures
Refining the Fields
Now that you’ve assigned fields to each table, you’ll refine the fields by
improving the field names and resolving any structural problems that
may exist. Then you’ll refine the tables further by establishing that
you’ve assigned the appropriate fields to each table and that the table
structures are sound.
Improving the Field Names
As you know, a field represents a characteristic of the subject of the ta-
ble to which it belongs. You can easily identify the characteristic a field
is supposed to represent when that field has an appropriate name. A
field name that is ambiguous, vague, or unclear is a sure sign of trouble
❖ Note Before you work through the remainder of the chapter, now is a good time to recall a principle I presented in the
Introduction:
Focus on the concept or technique and its intended results,
not on the example used to illustrate it.
I bring this to your attention once again because you’ll certainly
wonder why I created an example in a particular manner. Maybe
you’ve thought of a different or better approach to the problem,
and you might have thoroughly valid reasons for using it. But
don’t let the example mislead you. I’ve fashioned each example in
a specific manner for the sole reason of illustrating the concept
or technique at hand. Therefore, study the way that I correct the
problems you see in a particular example so that you can use
those techniques when you encounter similar problems in your
database.
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Refining the Fields 209
and suggests that you have not thoroughly identified the purpose of
the field.
Earlier in this chapter, you learned a set of guidelines for naming a
table. Now you’ll learn another set of guidelines that you’ll apply to
field names. Fortunately, many of them are similar to the guidelines
governing table names, so you’re already familiar with most of the
concepts.
Guidelines for Creating Field Names
• Create a unique, descriptive name that is meaningful to the entire
organization. A given field name should appear only once in the
entire database; the only exception to this rule occurs when the
field serves to establish a relationship between two tables. Make
certain the name is descriptive enough to convey its meaning ac-
curately to everyone who sees it. (Chapter 10 covers this issue in
greater detail.)
• Create a name that accurately, clearly, and unambiguously identi-
fies the characteristic a field represents. “Phone Number” is a good
example of an inaccurate, ambiguous field name. What kind of
phone number does it represent? A home phone? An office
phone? A cellular phone? Learn to be specific. If you need to
record each of these types of phone numbers, then create “Home
Phone,” “Work Phone,” and “Cellular Phone” fields.
In Chapter 6, you learned how to resolve generic field names,
such as “Address,” “City,” and “State” by using the table name as
a prefix for the field name. This produces names such as “Em-
ployee Address,” “Customer Address,” and “Supplier Address.”
When you have field names such as these, you can abbreviate the
prefix (for brevity’s sake) by using the first three or four letters of
the table name as the revised prefix. This allows you to transform
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210 Chapter 7 Establishing Table Structures
the previous field names into “EmpAddress,” “CustAddress,” and
“SuppAddress.” This technique helps you fulfill not only this
guideline, but the previous one as well.
• Use the minimum number of words necessary to convey the mean-
ing of the characteristic the field represents. You want to avoid
lengthy field names, but at the same time, you also want to avoid
using a single word as a field name if that word is inappropriate.
For example, if you’re trying to record the date a particular em-
ployee joined the organization, “Hired” is too short (and slightly
vague) and “Date That the Employee Was Hired” is too long! “Date
Hired,” however, is a more appropriate name and accurately rep-
resents the characteristic the field represents.
• Do not use acronyms, and use abbreviations judiciously. Acronyms
can be hard to decipher and often lead to misunderstanding.
Imagine a field named “CAD_SW.” How would you determine what
the field represents? On the other hand, you can use abbrevia-
tions so long as you use them sparingly and handle them with
care. Only use an abbreviation if it supplements or enhances the
field name in a positive manner. An abbreviation shouldn’t make
a field name ambiguous or diminish its meaning.
❖ Note The degree to which you use prefixes within a table is a matter of style. When a table contains generic field names, some
database designers will choose to prefix the generic names only,
while others elect to prefix all of the field names within the table.
Regardless of the prefix method you choose to use, it is very im-
portant that you use it consistently throughout the database
structure.
I personally prefer to prefix the generic field names only, and I’ll
follow this preference throughout the remainder of the book.
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Refining the Fields 211
• Do not use words that could confuse the meaning of the field name.
A field name that contains redundant words or synonyms can
make the name’s meaning unclear and subject to misinterpreta-
tion. For instance, consider the name “Digital Identification Code
Number.” “Digital” and “number” are redundant, so you can elimi-
nate either one without diminishing the field name’s meaning. Let’s
assume that you decide to eliminate “digital.” You can split the re-
maining name into two smaller names: “Identification Code” and
“Identification Number.” These names are often synonymous, and
you can easily use either as the final field name. In this situation,
just use the name that is most meaningful within the organization.
• Do not use names that implicitly or explicitly identify more than one
characteristic. These types of names are easy to spot because they
typically use the words “and” or “or.” Field names that contain a
slash (\) or an ampersand (&) are dead giveaways as well. When
you encounter a field with a name such as “Area or Location” or
“Phone\Fax,” identify each characteristic that the name implies,
and create a new field for the characteristic. Then test the new
field name against these guidelines to ensure that the name is
sound.
• Use the singular form of the name. A field with a plural name, such
as “Skills,” implies that it may contain two or more values for a
given record, which is not a good idea. (You’ll learn more about
this later in the chapter.) A field name is singular because it rep-
resents a single characteristic of the subject of the table to which
it belongs. A table name, on the other hand, is plural because it
represents a collection of similar objects or events. You can distin-
guish table names from field names quite easily when you use
this naming convention.
With these guidelines in mind, review each table and determine whe-
ther you can make improvements to any of the field names. When
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212 Chapter 7 Establishing Table Structures
you’re finished, you’re ready to identify and resolve any problems with
the fields. Figure 7.12 shows revisions to the field names of the table
structures in Figure 7.11.
In Figure 7.12, “Classes” is shortened to “Cls,” “Subjects” is shortened
to “Subj,” “Instructors” is shortened to “Inst,” “Student” is shortened to
“Std,” and “Social Security Number” replaces “SSN.” Remember that ab-
breviations can be very useful so long as they are meaningful and un-
derstood by everyone in the organization. Using proper and appropriate
abbreviations will not detract from the meaning of the field name.
❖ Note Throughout the remainder of the chapter and the rest of the book, table names within the text appear in all capital letters
(such as VENDORS) and field names within the text appear in
small capital letters (such as VENDOR ID NUMBER).
Figure 7.12. Revised field names.
Table Structures
InstName
InstAddress
InstPhone
InstSocial Security Number
Date Hired
Pay Rate
Instructors Students
StdName
StdAddress
StdPhone
StdSocial Security Number
Classes
ClsNumber
ClsName
Room Number
InstName
SubjName
Subjects
SubjName
SubjDescription
Category
Credits
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Refining the Fields 213
Using an Ideal Field to Resolve Anomalies
Although you’ve carefully identified the fields on your preliminary field
list, you may have created a few fields that could prove problematic to
the table structure. Poorly defined fields can cause duplicate data and
redundant data, and they can be difficult to use. You might find it diffi-
cult to determine whether any of the fields in a table is going to cause
problems unless you know the warning signs. The best way to identify
potentially troublesome fields is to determine whether they comply with
the Elements of the Ideal Field. These elements constitute a set of guide-
lines you can use to create sound field structures and to spot poorly de-
signed fields easily.
Elements of the Ideal Field
• It represents a distinct characteristic of the subject of the table. As
you know, a table represents a specific subject, which can be an
object or event. The ideal field represents a distinct characteristic
of that object or event.
• It contains only a single value. A field that can potentially store
two or more occurrences of the same value is known as a multival-
ued field. A multivalued field causes data-redundancy problems
(quite obviously) and is difficult to use when you try to edit, de-
lete, or sort the data within it. The ideal field is free of these prob-
lems because it contains only a single value.
• It cannot be deconstructed into smaller components. A field that
can potentially store two or more distinct items within a value is
known as a multipart (or composite) field. Like the multivalued
field, this type of field causes problems when you try to edit, de-
lete, or sort the data within it. These problems don’t occur with an
ideal field because it represents a single, distinct characteristic of
the subject of the table to which it belongs. (You’ll learn more
about multivalued and multipart fields in just a moment.)
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214 Chapter 7 Establishing Table Structures
• It does not contain a calculated or concatenated value. The values
of the fields in a table should be mutually independent; a particu-
lar field should not have to depend on the values of other fields for
its own value. A calculated field, however, does depend on the val-
ues of other fields for its own value, and therein lies the problem.
The calculated field’s value is not updated when the value of any
field participating in the calculation changes. It then becomes the
responsibility (and an undesirable burden) of the user or the da-
tabase application program to update the calculated field when
this type of change takes place. This is precisely why you deal
with calculated fields separately.
• It is unique within the entire database structure. The only dupli-
cate fields that appear in a properly designed database are those
that establish relationships between tables. If duplicate fields
other than these exist in a table, it is very likely that the table will
accumulate unnecessary redundant data and that the data within
the duplicate fields will inevitably become inconsistent.
• It retains a majority of its properties when it appears in more than
one table. A field that establishes a relationship between two
tables is a structural component of each table. A majority of the
field’s properties remain constant in each occurrence of the field.
(Chapters 9 and 10 cover this matter in greater detail.)
❖ Note Remember that you’re dealing strictly with the logi- cal database structure at this point. You might have cause
to duplicate specific fields when you physically implement
the database in an RDBMS program. During that process,
however, you’re making a conscious decision to duplicate
the fields, and you’re prepared to deal with the conse-
quences of that decision.
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Refining the Fields 215
Although you now know the specific elements of an ideal field, you’ll still
find it difficult in many instances to identify problematic fields just by
looking at their names. Figure 7.13 shows a table structure that helps to
illustrate this point. Take a moment and try to determine whether each
field complies with the Elements of the Ideal Field or needs to be modified.
Each field on the list seems to conform to the Elements of the Ideal Field.
Examine the list carefully, however, and you’ll see that some fields don’t
really comply with the second and third elements. Three fields have
anomalies that will cause problems unless you resolve them: INSTNAME,
INSTADDRESS, and CATEGORIES TAUGHT. If you doubt this assertion, you can
test it by “loading” the table with sample data. This will quickly reveal
anomalies, if any exist, and is the best way to confirm whether a field
complies with all of the Elements of the Ideal Field.
You don’t have to create a table physically to perform this test. Take a
sheet of legal paper and lay it in front of you lengthwise from left to right.
Figure 7.13. A table containing fields with questionable structures.
Table Structures
Instructors
InstName
InstAddress
InstPhone
InstSocial Security Number
Date Hired
Pay Rate
Categories Taught
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216 Chapter 7 Establishing Table Structures
Write the name of each field across the top of the paper, starting from the
left-hand side; leave enough space between the field names to allow
room for the values you’re going to place underneath them. Then enter
records into the table by filling in each field with some sample data; be
sure the sample data represents the data you’re actually going to enter
into the database. You need only a few records for the test to work prop-
erly. Your sheet of paper should look similar to the one in Figure 7.14.
Now you can easily identify which fields are going to be troublesome un-
less they are resolved. As you can see, INSTNAME and INSTADDRESS are
both multipart fields, and CATEGORIES TAUGHT is a multivalued field. You
must resolve these fields before you can refine the table structure.
Resolving Multipart Fields
Working with a multipart field is difficult because its value contains two
or more distinct items. It’s hard to retrieve information from a multipart
❖ Note As I mentioned in Chapter 3, I show only those fields that are most relevant to the discussion at hand and use <<other
fields>> to represent fields that are inessential to the example.
Figure 7.14. Testing a table with sample data.
Instructors
<< other fields >>
......
......
......
......
InstPhone
363-9948
527-4992
336-5992
322-6992
InstAddress
3131 Mockingbird Lane, Seattle, WA 98157
7402 Kingman Drive, Redmond, WA 98115
4141 Lake City Way, Seattle, WA 98136
970 Phoenix Avenue, Bellevue, WA 98046
Categories Taught
DTP, SS, WP
WP, DB, OS
DB, SS
DTP, WP, PG
InstName
Shannon McLain
Estela Pundt
Timothy Ennis
Kendra Bonnicksen
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Refining the Fields 217
field, and it’s hard to sort or group the records in the table by the field’s
value. The INSTADDRESS field in Figure 7.14 illustrates these difficulties;
you’d certainly have a problem retrieving information for the city of Se-
attle or sorting information by zip code.
You resolve a multipart field by identifying the distinct items within the
field’s value and treating each item as an individual field. Accomplish
this task by asking yourself a simple question: “What specific items
does this field’s value represent?” Once you’ve answered the question
and identified the items (as best you can), transform each item into a
new field.
In Figure 7.14, the value of the field INSTNAME represents two items: the
first name and the last name of an instructor. You resolve this field by
creating a new INSTFIRST NAME field and a new INSTLAST NAME field. The
value of INSTADDRESS represents four items: the street address, city,
state, and zip code of an instructor. You transform these items into
fields as well; they will appear in the table as INSTSTREET ADDRESS, IN-
STCITY, INSTSTATE, and INSTZIPCODE. Figure 7.15 shows the newly revised
INSTRUCTORS table.
Figure 7.15. Resolving the multipart fields in the INSTRUCTORS table.
Instructors
InstFirst Name InstLast Name InstStreet Address InstCity InstState InstZipcode InstPhone Categories Taught << other fields >>
Kendra Bonnicksen 3131 Mockingbird Lane Seattle WA 98157 363-9948 DTP, SS, WP ......
Timothy Ennis 7402 Kingman Drive Redmond WA 98115 527-4992 WP, DB, OS ......
Shannon McLain 4141 Lake City Way Seattle WA 98136 336-5992 DB, SS ......
Estela Pundt 970 Phoenix Avenue Bellevue WA 98046 322-6992 DTP, WP, PG ......
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218 Chapter 7 Establishing Table Structures
Some multipart fields are hard to recognize. Take a look at the INSTRU-
MENTS table in Figure 7.16. At first glance, the table doesn’t seem to
contain multipart fields. When you examine the data in the table more
closely, however, you’ll see that INSTRUMENT ID is actually a multipart
field. This field’s value represents two distinct items: the category to
which the instrument belongs—AMP (amplifier), GUIT (guitar), MFX
(multieffects unit), SFX (single-effect unit)—and the instrument’s identi-
fication number. Clearly, you should deconstruct INSTRUMENT ID into two
smaller fields in accordance with the third element of an ideal field.
Imagine how difficult it would be for you to update the field’s value if the
MFX category changed to MFU if you don’t do this. You would have to
write programming code to parse the value, test for the existence of
MFX, and then replace it with MFU if it existed within the parsed value.
It’s not so much that you can’t do this, but you would definitely be
working harder than necessary, and you shouldn’t have to go through
this at all if you have a properly designed database.
Figure 7.16. An example of a “hidden” multipart field.
Instrument ID Manufacturer Instrument Description
Instruments
<< other fields >>
Player 2100 MultieffectsZoomMFX3349 ......
JCM 2000 Tube Super LeadMarshallAMP1001 ......
VC60 Pro Tube AmpCrateAMP5590 ......
Cry Baby Wah-WahDunlopSFX2227 ......
Twin Reverb ReissueFenderAMP2766 ......
GUIT = Category (“Guitar”) 2201 = Identification Number
StratocasterFender ......GUIT2201
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Refining the Fields 219
Resolving Multivalued Fields
As you know, a multivalued field can potentially store two or more oc-
currences of the same value. Fortunately, you’ll recognize a multivalued
field when you see one. The field’s name is often plural and its value al-
most invariably contains a number of commas, which serve to separate
the various occurrences that exist within the value itself.
Resolving multipart fields is not very hard at all, but resolving multival-
ued fields can be a little more difficult and will take some work. A mul-
tivalued field has the same fundamental set of problems as a multipart
field, as the CATEGORIES TAUGHT field in Figure 7.17 clearly illustrates.
For example, you’ll have difficultly retrieving information for everyone
who teaches a specific category (such as WP), you can’t sort the data in
any meaningful fashion, and, most important, you don’t have room to
enter more than four categories. What happens when one or more in-
structors teach five categories? The only option you’ll have is to make
the field larger every time you need to enter more values than it will
currently allow.
Figure 7.17. Identifying a multivalued field.
Instructors
InstStreet Address
3131 Mockingbird Lane
7402 Kingman Drive
4141 Lake City Way
970 Phoenix Avenue
InstCity
Seattle
Redmond
Seattle
Bellevue
InstFirst Name
Shannon
Estela
Timothy
Kendra
InstLast Name
McLain
Pundt
Ennis
Bonnicksen
<< other fields >>
......
......
......
......
Categories Taught
DB, SS
DTP, WP, PG
DTP, SS, WP
WP, DB, OS
Commas separate the occurrences within this value.
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220 Chapter 7 Establishing Table Structures
So how would you resolve this multivalued field? Your first thought may
be to create a new field for each value, thus “flattening” the multivalued
field into several single-valued fields. Figure 7.18 shows what will hap-
pen if you follow through with this idea.
Unfortunately, this is not much of an improvement at all. There are
three specific problems that arise from this type of structure:
1. Retrieving category information will be tedious at best. A user
attempting to find all instructors who teach the WP category must
be sure to search for this value within each of the category fields—
there is no guarantee that WP is consistently stored in the same
field. Failure to do so means that the user runs the risk of over-
looking a qualified instructor.
2. There is no way for the RDBMS program to sort the category data in
a meaningful fashion.
3. This structure is inherently volatile. In its current state, the table
unnecessarily restricts the number of categories an instructor can
teach; you must create additional category fields when you have
instructors who teach more than three categories. Adding more
category fields just compounds the first two problems.
Realizing that flattening the CATEGORIES TAUGHT field won’t solve your prob-
lem, your next thought is to bring the field into compliance with the sec-
Figure 7.18. The result of “flattening” the CATEGORIES TAUGHT field.
Instructors
Category Taught 1
DTP
WP
DB
InstFirst Name
Shannon
Timothy
Kendra
InstLast Name
McLain
Ennis
Bonnicksen
InstStreet Address
3131 Mockingbird Lane
7402 Kingman Drive
4141 Lake City Way
InstCity
Seattle
Redmond
Seattle
Category Taught 2
SS
DB
SS
Category Taught 3
WP
OS
<< other fields >>
......
......
......
970 Phoenix Avenue BellevueEstela Pundt ...... DTP WP PG
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Refining the Fields 221
ond element of an ideal field and declare that it will contain only a single
value. Although this is a good impulse and a step in the right direction, it
will not resolve the matter completely because it will introduce yet an-
other problem: data redundancy. Figure 7.19 illustrates what happens
when you follow through with this particular idea. Note that there is now
a single value in the CATEGORIES TAUGHT field for each record in the table.
The values in CATEGORIES TAUGHT cause redundant data because you
must duplicate a given instructor record for each category that the in-
structor teaches. This redundancy is obviously unacceptable, so you’ll
have to resolve this problem in some other manner.
You can avoid this situation entirely by using these steps to resolve a
multivalued field:
1. Remove the field from the table and use it as the basis for a new
table. If necessary, rename the field in accordance with the field
name guidelines that you learned earlier in this chapter.
Figure 7.19. The result of bringing CATEGORIES TAUGHT into compliance with the second element of an ideal field.
Instructors
InstPhone
363-9948
527-4992
336-5992
Categories Taught
DTP
DB
DB
InstFirst Name
Shannon
Timothy
Kendra
InstLast Name
McLain
Ennis
Bonnicksen
InstStreet Address
3131 Mockingbird Lane
7402 Kingman Drive
4141 Lake City Way
InstState
WA
WA
WA
InstCity
Seattle
Redmond
Seattle
InstZipcode
98157
98115
98136
363-9948 SSKendra Bonnicksen 3131 Mockingbird Lane WASeattle 98157
363-9948 WPKendra Bonnicksen 3131 Mockingbird Lane WASeattle 98157
527-4992 OSTimothy Ennis 7402 Kingman Drive WARedmond 98115
527-4992 WPTimothy Ennis 7402 Kingman Drive WARedmond 98115
322-6992 DTPEstela Pundt 970 Phoenix Avenus WABellevue 98046
336-5992 SSShannon McLain 4141 Lake City Way WASeattle 98136
322-6992 WPEstela Pundt 970 Phoenix Avenus WABellevue 98046
322-6992 PGEstela Pundt 970 Phoenix Avenus WABellevue 98046
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222 Chapter 7 Establishing Table Structures
2. Use a field (or set of fields) from the original table to relate the orig-
inal table to the new table; try to select fields that represent the
subject of the table as closely as possible. The field(s) you choose
will appear in both tables. (You’ll learn more about relating tables
in Chapter 10.)
3. Assign an appropriate name, type, and description to the new
table and add it to the final table list.
These steps form a generic procedure that you can use to resolve any
multivalued field you encounter in a table. Now, apply these steps to the
CATEGORIES TAUGHT field.
1. Remove the field from the INSTRUCTORS table and use it as the
basis of a new table. Because this will now be a single-valued field,
rename the field CATEGORY TAUGHT.
2. Use INSTFIRST NAME and INSTLAST NAME as the connecting fields that
will relate the INSTRUCTORS table to the new table, and add them
to the structure of the new table.
3. Give the new table a proper name, compose a suitable descrip-
tion, and add the table to the final table list. (Indicate the table’s
type as “Data.”) Here’s one possible name and description you
might use for the new table.
Instructor Categories—the categories of software programs
that an instructor is qualified to teach. The information this
table provides allows us to make certain that there is an ade-
quate number of instructors for each software category.
Figure 7.20 shows the revised INSTRUCTORS table and the new IN-
STRUCTOR CATEGORIES table.
Note that the new INSTRUCTOR CATEGORIES table is free from the
problems typically associated with multivalued fields because CATEGORY
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Refining the Fields 223
TAUGHT is a single-value field. You can easily retrieve information for a
particular instructor or category, and you can sort the records in a
meaningful manner. Also note that the INSTFIRST NAME and INSTLAST NAME
fields retain their names in the new table, making them compliant with
the fifth element of an ideal field.
Although the new table contains redundant data, the redundancy is ac-
ceptable because it is minimal. It’s a fact of life that a relational data-
base will always contain some amount of redundant data. Your goal as
the database architect is to make certain that it has only an absolute
minimum amount of redundant data.
Figure 7.20. Resolving the multivalued field in the INSTRUCTORS table.
Instructors
InstPhoneInstFirst Name InstLast Name InstStreet Address InstStateInstCity InstZipcode
363-9948Kendra Bonnicksen 3131 Mockingbird Lane WASeattle 98157
527-4992Timothy Ennis 7402 Kingman Drive WARedmond 98115
336-5992Shannon McLain 4141 Lake City Way WASeattle 98136
322-6992Estela Pundt 970 Phoenix Avenue WABellevue 98046
Category Taught
Instructor Categories
InstFirst Name InstLast Name
Kendra Bonnicksen DTP
Kendra Bonnicksen SS
Kendra Bonnicksen WP
Timothy Ennis WP
Timothy Ennis DB
Timothy Ennis OS
Shannon McLain DB
Shannon McLain SS
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224 Chapter 7 Establishing Table Structures
Figure 7.21 shows a version of the INSTRUCTORS table that contains
three multivalued fields:
CATEGORIES TAUGHT—This indicates the categories of classes that
an instructor can teach.
MAXIMUM LEVEL TAUGHT—This indicates the maximum skill level
that the instructor can teach for a given category.
LANGUAGES SPOKEN—This indicates the foreign languages that an
instructor can speak.
Your task here seems relatively clear—you’re going to use the procedure
you’ve just learned to resolve these multivalued fields. You then notice
one small, relatively obscure problem: There is a distinct one-to-one as-
sociation between values in CATEGORIES TAUGHT and the values in MAXIMUM
LEVEL TAUGHT for any given record. You probably wouldn’t have noticed
this anomaly had you not carefully examined the sample data within
these fields. Don’t worry; you’ll still use the same procedure, but with
one minor modification.
You’ll occasionally encounter a situation such as this, where some given
field (whether single- or multivalued) depends on a particular multival-
ued field. You can easily fix this problem by including the dependent
Figure 7.21. A version of the INSTRUCTORS table containing three multivalued fields.
Instructors
Campus Phone
363-9948
527-4992
336-5992
322-6992
Categories Taught
DTP, OS, SS, WP
DB, OS, UT, WP
DB, PG, SS
DTP, PG, WP
InstFirst Name
Shannon
Estela
Timothy
Kendra
InstLast Name
McLain
Pundt
Ennis
Bonnicksen
Maximum Level Taught
Intermediate, Basic, Advanced, Basic
Intermediate, Basic, Basic, Advanced
Advanced, Intermediate, Intermediate
Basic, Intermediate, Basic
Languages Spoken
French, Spanish
German, Spanish
French, German
French, Italian, Spanish
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Refining the Fields 225
field in the structure of the new table you build to resolve the multival-
ued field. Figure 7.22 shows the results of consolidating this technique
with the previous one to resolve CATEGORIES TAUGHT. (It shows the resolu-
tion of LANGUAGES SPOKEN as well.)
The redundancy in the new tables is acceptable because, once again, it
is minimal. In Chapter 10, you’ll learn how to reduce this type of re-
dundancy even further by relating the tables with primary keys and
foreign keys.
Figure 7.22. Resolving the multipart fields in the INSTRUCTORS table.
Instructors
Campus PhoneInstFirst Name InstLast Name
336-5992Shannon McLain
322-6992Estela Pundt
527-4992Timothy Ennis
363-9948Kendra Bonnicksen
Language Spoken
Instructor Languages
InstFirst Name
Kendra
InstLast Name
Bonnicksen
Shannon
Kendra
McLain
Bonnicksen
Timothy Ennis
Timothy Ennis
Shannon McLain
Estela Pundt
Estela Pundt
French
Spanish
German
Spanish
French
German
French
Italian
Estela Pundt Spanish
Category Taught
Instructor Categories
InstFirst Name
Kendra
InstLast Name
Bonnicksen
Timothy
Kendra
Ennis
Bonnicksen
Kendra Bonnicksen
Kendra Bonnicksen
Timothy Ennis
Timothy Ennis
Timothy Ennis
DTP
OS
SS
WP
DB
OS
UT
WP
Maximum Level
Intermediate
Advanced
Basic
Advanced
Intermediate
Basic
Basic
Advanced
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Refining the Table Structures
Now that you’ve refined the fields and made certain that each field is
sound, you can begin the process of refining the table structures. Your
objective in this phase of the design process is to make sure that you’ve
assigned the appropriate fields to each table and that you’ve properly
defined each table’s structure. This process will also reveal whether the
tables have anomalies that you need to resolve.
A Word About Redundant Data and Duplicate Fields
You’ve seen the term redundant data used quite often in this chapter.
Redundant data was characterized as being unacceptable in many
cases, but appropriate in others. In order for you to better understand
how to determine when redundant data is acceptable, a definition of the
term is in order.
Redundant data is a value that is repeated in a field as a result of the
field’s participation in relating two tables or as a result of some field or
table anomaly. In the first instance, the redundant data is appropri-
ate; by definition, a field used to relate one table to another will con-
tain redundant data. (You’ll learn more about this in Chapter 10.)
Redundant data is entirely unacceptable in the second instance, how-
ever, because it poses problems with data consistency and data integ-
rity; therefore, you should always strive to keep redundant data to an
absolute minimum.
A duplicate field is a field that appears in two or more tables for any of
these reasons:
• It is used to relate a set of tables together.
• It indicates multiple occurrences of a particular type of value.
• There is a perceived need for supplemental information.
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Refining the Table Structures 227
The only instance in which a duplicate field is necessary is when it
serves to establish a relationship between two tables; it provides the sole
means of associating records in the first table with records in the second
table. Duplicate fields are unnecessary in all other cases, and you
should avoid them because they introduce needless, redundant data.
As you refine each table structure, you’ll assess whether to retain a
given duplicate field in the table. If the reason for its existence in the ta-
ble is valid, then you’ll keep it; otherwise, you’ll remove it. You’ll learn
how to deal effectively with both redundant data and unnecessary du-
plicate fields in the following sections.
Using an Ideal Table to Refine Table Structures
Despite your efforts to refine the fields in a table, the table structure it-
self may contain anomalies that can produce unnecessary redundant
data and make it difficult to work with the data in the table. You can
identify a potentially problematic table structure by determining
whether it complies with the Elements of the Ideal Table. These ele-
ments constitute a set of guidelines you can use to create sound table
structures and to spot poorly designed tables easily.
Elements of the Ideal Table
• It represents a single subject, which can be an object or event. Yes,
I know, I’ve said this a number of times already. The fact of the
matter is that I can’t overemphasize this point. As long as you
guarantee that each of your tables represents a single subject,
you greatly reduce the risk of potential data-integrity problems.
This element validates the work you’ve done during the analysis
and interview stages of the database-design process, as well as
the work you’ve just recently performed.
• It has a primary key. This is important for two reasons: It
uniquely identifies each record within a table, and it plays a key
From the Library of Stephen Benoit
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228 Chapter 7 Establishing Table Structures
role (no pun intended) in establishing table relationships. Addi-
tionally, it has specific characteristics that help to implement and
enforce various levels of data integrity. If you fail to assign a pri-
mary key to each table, you will eventually have data-integrity
problems. Chapter 8 covers primary keys in greater detail.
• It does not contain multipart or multivalued fields. Theoretically,
you should have resolved these issues when you refined the field
structures. Nevertheless, it’s still a good idea to review the fields
one last time to ensure that you’ve completely removed each and
every one of them.
• It does not contain calculated fields. Although you might believe
that your current table structures are free of calculated fields, you
may have accidentally overlooked one or two calculated fields dur-
ing the field refinement process. This is a good time to review the
table structures once more and make certain you remove those
calculated fields you may have missed.
• It does not contain unnecessary duplicate fields. (Note that this
guideline does not apply to fields used to relate a set of tables to-
gether, such as those used in the example in Figure 7.22.) One of
the hallmarks of a poorly designed table is the inclusion of dupli-
cate fields from other tables. You might feel compelled to add du-
plicate fields to a table for one of two reasons: to provide reference
information or to indicate multiple occurrences of a particular
type of value. Duplicate fields such as these raise various difficul-
ties when you work with the data or attempt to retrieve informa-
tion from the table.
• It contains only an absolute minimum amount of redundant data.
Remember that a relational database will never be completely free
of redundant data. But you can—and should—make certain that
each table contains as little redundant data as possible.
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Refining the Table Structures 229
Resolving Unnecessary Duplicate Fields
Before you make final modifications to the table structures, you must
first remove all unnecessary duplicate fields from the database. You can
then refine the tables so that they comply with the Elements of the Ideal
Table.
Duplicate fields that serve to provide reference information (also known
as reference fields) are unnecessary and easy to resolve—you just re-
move them from the table. Unfortunately, many people believe that a ta-
ble must contain every field that will appear in the reports they generate
from it, so they introduce various duplicate fields into the table as they
deem necessary. They assume that the table will then be able to provide
all the requisite information for their reports. But they are mistaken,
and their action is both unwise and undesirable. Tables containing ref-
erence fields exhibit poor design and will have a number of problems,
many of which will become increasingly clear as the database-design
process unfolds. Reference fields force the user or database application
program to ensure that the values in all occurrences of the field are mu-
tually consistent, a process that carries a high risk of error. Figure 7.23
shows an example of a table containing reference fields.
The MANPHONE and WEB SITE fields in the INSTRUMENTS table are refer-
ence fields and, by definition, are actually unnecessary duplicate fields.
You certainly don’t need to include them in this table because they’re al-
ready part of the MANUFACTURERS table structure; therefore, you can
remove them from the INSTRUMENTS table in order to resolve the un-
necessary duplication problem. (MANUFACTURER is not a reference field be-
cause it currently relates the INSTRUMENTS table to the
MANUFACTURERS table.) You’ll learn later in Chapter 12 that you can
work with fields from the INSTRUMENTS table and the MANUFACTUR-
ERS table at the same time by combining them within a view (virtual ta-
ble). You can then use this view as the basis for compiling any reports
you require.
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2 3
0 C
h a
p ter 7
E sta
b lish
in g T
a b le S
tru ctu
res
Figure 7.23. Example of a table containing reference fields.
Manufacturers
ManPhone
745-2722
596-9690
778-6565
364-2244
Manufacturer
Mesa/Boogie
Samson Technologies Corp.
Fender Musical Instruments
Dunlop Manufacturing, Inc.
ManStreet Address
PO Box 846
8860 E. Chaparral Road
1317 Ross Street
PO Box 9031
ManState
CA
AZ
CA
NY
ManCity
Benicia
Scottsdale
Petaluma
Syosset
ManZipcode
94510
85250
94954
11791
738-7563St. Louis Music, Inc. 1400 Ferguson Avenue MOSt. Louis 63133
Web Site
www.jimdunlop.com
www.fender.com
www.mesaboogie.com
www.samsontech.com
www.crateamps.com
Instruments
Instrument ID
2201
3349
1001
5590
2227
2766
Instrument Description
Stratocaster
Player 2100 Multi-Effects
JCM 2000 Tube Super Lead
Crate VC60 Pro Tube Amp
Cry Baby Wah-Wah
Twin Reverb Reissue
Amplifier
Amplifier
Single-Effect Unit
Amplifier
Category
Guitar
Multi-Effect Unit
Web Site
www.jimdunlop.com
www.fender.com
www.mesaboogie.com
www.samsontech.com
www.crateamps.com
ManPhone
745-2722
596-9690
778-6565
364-2244
738-7563
www.fender.com596-9690
Manufacturer
Fender Musical Instruments
Samson Technologies Corp.
Mesa/Boogie
St. Louis Music, Inc.
Dunlop Manufacturing, Inc.
Fender Musical Instruments
$ 549.99
$ 399.99
$ 169.99
$ 1,224.99
Price
$ 799.99
$ 174.99
These fields duplicate the MANPHONE and WEB SITE fields in the MANUFACTURERS table.
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Refining the Table Structures 231
Duplicate fields that serve to indicate multiple occurrences of the same
type of value are unnecessary as well. For example, take a look at the
version of the STUDENTS table presented in Figure 7.24.
INSTRUMENT 1, INSTRUMENT 2, and INSTRUMENT 3 are duplicate fields that repre-
sent multiple occurrences of the same type of value. Their purpose in the
table is to enable the music department to keep track of the instruments
checked out by a given student. Aside from the difficulties these fields
pose in retrieving information about a particular instrument, the fields
also limit the number of instruments a student can check out. What hap-
pens if several students want to check out more than three instruments?
Does this type of field structure look strangely familiar? It should! It’s
similar to the one back in Figure 7.18. As you’ve probably already
guessed, it’s nothing more than a flattened multivalued field. Mind you,
the person who created this table probably didn’t have a multivalued
field in mind (and neither do most folks who create fields such as these),
but that is what it truly is.
You already know how to deal with these unnecessary duplicate fields
because you know how to resolve multivalued fields. You can easily fix
Figure 7.24. A simple example of a table containing unnecessary duplicate fields.
Students
Instrument 1 Instrument 2 Instrument 3
These duplicate fields represent three occurrences of the same type of value.
StdFirst Name StdLast Name StdStreet Address << other fields >>
Guitar Tenor SaxScott Barker 2904 Madison Ave ......
Tenor Sax Clarinet Electric PianoMichael Chow 7410 Taxco Drive ......
Drum Set Bass GuitarDebbie McGuire 332 158th Ave SE ......
Guitar Electric Piano Snare DrumAngie Thomson 970 Pine Blvd ......
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232 Chapter 7 Establishing Table Structures
the STUDENTS table by first visualizing the INSTRUMENT 1, INSTRUMENT 2,
and INSTRUMENT 3 fields as a singular multivalued field, and then resolv-
ing it as you would any multivalued field. Figure 7.25 illustrates this
process. The shaded version of the STUDENTS table shows how you vi-
sualize the instrument fields as a singular multivalued field. You then
resolve the multivalued field by applying the three-step process you
learned earlier, which yields the revised STUDENTS table and the new
STUDENT INSTRUMENTS table. When you’re finished, you’ll be able to
enter any number of instruments for a particular student. It will then be
quite easy for you to retrieve information such as the names of the stu-
dents who have checked out a guitar, a list of the instruments that are
currently checked out by a particular student, and the number of stu-
dents who have checked out an electric piano.
Figure 7.25. Resolving a simple set of unnecessary duplicate fields.
Student Instruments
Instrument
Guitar
Tenor Sax
Clarinet
Electric Piano
Tenor Sax
Drum Set
Bass Guitar
StudLast Name
Barker
Chow
McGuire
Barker
Chow
Chow
McGuire
StudFirst Name
Scott
Michael
Debbie
Scott
Michael
Michael
Debbie
Students
StdFirst Name
Scott
Michael
Debbie
Angie
StdLast Name
Barker
Chow
McGuire
Thomson
StdStreet Address
2904 Madison Ave
7410 Taxco Drive
332 158th Ave SE
970 Pine Blvd
<< other fields >>
......
......
......
......
Students
StdFirst Name StdLast Name StdStreet Address << other fields >> Instruments
Scott Barker 2904 Madison Ave ...... Guitar, Tenor Sax
Michael Chow 7410 Taxco Drive ...... Tenor Sax, Clarinet, Electric Piano
Debbie McGuire 332 158th Ave SE ...... Drum Set, Bass Guitar
Angie Thomson 970 Pine Blvd ...... Guitar, Electric Piano, Snare Drum
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Refining the Table Structures 233
In some instances, a table can contain two or more sets of duplicate
fields that represent multiple occurrences of the same type of value. Fig-
ure 7.26 shows a slightly different version of the STUDENTS table shown
in Figure 7.24; this version contains two sets of duplicate fields. You
may be thinking at this very moment, “Why is he saying there are two
sets of duplicate fields when I clearly see three?” Contrary to what you
may think, INSTRUMENT 1/CHECKOUT DATE 1, for example, does not consti-
tute a set of duplicate fields. Quite the opposite—INSTRUMENT 1/INSTRUMENT
2/INSTRUMENT 3 constitute the first set of duplicate fields, and CHECKOUT
DATE 1/CHECKOUT DATE 2/CHECKOUT DATE 3 constitute the second set of du-
plicate fields.
You’ve probably realized that these two sets of duplicate fields are actu-
ally two flattened multivalued fields and that you can resolve them in
the same manner as in the previous example. The only other issue that
you must be concerned with is the distinct one-to-one association be-
tween an instrument and a checkout date. This won’t be a problem,
however, because you’ve dealt with this type of scenario before. If you vi-
sualize one multivalued field called INSTRUMENTS and another called
CHECKOUT DATE, you’ll see that the overall table structure is quite similar
to the one in Figure 7.21. (There’s a one-to-one association between the
CATEGORIES TAUGHT and MAXIMUM LEVEL TAUGHT fields.)
Figure 7.26. Example of a table with multiple sets of duplicate fields.
Students
StdFirst Name
Scott
Michael
Debbie
Angie
StdLast Name
Barker
Chow
McGuire
Thomson
<< other fields >>
......
......
......
......
Instrument 1
Guitar
Tenor Sax
Drum Set
Guitar
Instrument 2
Tenor Sax
Clarinet
Bass Guitar
Electric Piano
Instrument 3
Electric Piano
Snare Drum
Checkout Date 1
09/26/01
09/26/01
11/14/01
11/14/01
Checkout Date 2
09/28/01
10/03/01
11/20/01
11/14/01
Checkout Date 3
10/16/01
12/05/01
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234 Chapter 7 Establishing Table Structures
Figure 7.27 illustrates how you can fix this table. As before, the shaded
version of the STUDENTS table shows how you visualize the instrument
and checkout date fields as singular multivalued fields. You then re-
solve the multivalued fields by applying the three-step process you
learned earlier, yielding the revised STUDENTS table and the new STU-
DENT INSTRUMENTS table.
Now that you’re familiar with the Elements of the Ideal Table, review
your table structures and refine them as necessary. When you’re in
Figure 7.27. Resolving the multiple sets of duplicate fields in the STUDENTS table.
Students
StdFirst Name
Scott
Michael
Debbie
Angie
StdLast Name
Barker
Chow
McGuire
Thomson
StdStreet Address
2904 Madison Ave
7410 Taxco Drive
332 158th Ave SE
970 Pine Blvd
<< other fields >>
......
......
......
......
Students
StdFirst Name StdLast Name << other fields >> Checkout DatesInstruments
Scott Barker ...... 09/26/01, 09/28/01Guitar, Tenor Sax
Michael Chow ...... 09/28/01, 10/03/01, 10/16/01Tenor Sax, Clarinet, Electric Piano
Debbie McGuire ...... 11/14/01, 11/20/01Drum Set, Bass Guitar
Angie Thomson ...... 11/14/01, 11/14/01, 12/05/01Guitar, Electric Piano, Snare Durm
Student Instruments
Instrument
Guitar
Tenor Sax
Clarinet
Electric Piano
Tenor Sax
Drum Set
Bass Guitar
StudLast Name
Barker
Chow
McGuire
Barker
Chow
Chow
McGuire
StudFirst Name
Scott
Michael
Debbie
Scott
Michael
Michael
Debbie
Checkout Date
09/26/01
10/03/01
09/28/01
09/28/01
10/16/01
11/14/01
11/20/01
From the Library of Stephen Benoit
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Refining the Table Structures 235
doubt about a particular table, sketch its structure on a piece of paper
and load it with sample data. You’ll then be able to resolve the anoma-
lies revealed by the data.
Establishing Subset Tables
As you refine the structures of your tables, you may find that some of
the fields in a particular table do not always contain values. This situa-
tion will not affect your ability to retrieve information from the table, but
it can indicate that the table might need further refinement. Consider
the structure of the INVENTORY table in Figure 7.28.
In this scenario, the table contains data about various items in a per-
son’s office, such as office furniture, office equipment (computers,
faxes, and so forth), and books. It’s inevitable that the values of several
fields in many of the records will be blank. For example, a book will not
Figure 7.28. Structure of an office inventory table.
Table Structures
Inventory
Item Name Model
Item Description Warranty Expiration Date
Current Value Publisher
Insured Value Author
Date Entered ISBN
Manufacturer Category
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236 Chapter 7 Establishing Table Structures
have a MANUFACTURER, MODEL, or WARRANTY EXPIRATION DATE, and a fax ma-
chine will not have an AUTHOR, PUBLISHER, ISBN, or CATEGORY. This doesn’t
pose a problem from a physical viewpoint (limited hard-disk space isn’t
the critical issue it was in years past), but it can pose a perceptual prob-
lem. Users (and management, for that matter) get fairly nervous when
they see a lot of blank values in a table. Is the data missing? Did some-
one forget to make entries into these fields? Has someone mistakenly
deleted the data? Did the computer accidentally destroy the original val-
ues? (Yes, the urban myth, “The computer did it!” still lives on.) The
more important question is this: If you were adhering to the Elements of
the Ideal Table as you were creating this table, how did you arrive at
this particular structure?
Fortunately, this is just another type of structural anomaly that occa-
sionally occurs as you design various tables. Your task now is to learn
how to deal with it in an appropriate manner.
The first step is to determine whether the INVENTORY table truly com-
plies with the first element of an ideal table (i.e., “It represents a single
subject”). A table that contains a large number of blank values in its
fields usually—but not always—represents more than one subject.
Think about the two sets of fields in question for a moment, and you’ll
soon realize that they represent characteristics of two distinct aspects of
the table’s subject. The first set of fields describes equipment inventory,
and the second set of fields describes books inventory; furthermore,
both types of inventory share common characteristics, such as ITEM
NAME, ITEM DESCRIPTION, and CURRENT VALUE. In essence, “Equipment” and
“Books” are subjects that are dependent upon the INVENTORY table for
their very existence; neither describes a completely distinct object or
event. As a result, they are subordinate subjects, and you’ll create a sub-
set table for each of them.
Just as a data table represents a distinct subject, a subset table repre-
sents a subordinate subject of a particular data table. The subset table
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Refining the Table Structures 237
contains fields that are germane to the subordinate subject it repre-
sents, and it also includes a field (or fields) from the data table that
serves to relate the data table to the subset table. It’s important to note
that a subset table does not contain fields that represent characteristics
common to both it and the data table; these fields must remain in the
data table.
Now that you’ve determined that the INVENTORY table describes three
subjects (it doesn’t matter that two of them are subordinate subjects),
you must bring it into compliance with the first element of an ideal table
by removing the fields in question. You then use the fields as the basis
for two new subset tables, one for each subordinate subject. Here are
the steps you follow to accomplish these tasks:
1. Use the MANUFACTURER, MODEL, and WARRANTY EXPIRATION DATE fields to
create a new subset table called EQUIPMENT.
2. Use the PUBLISHER, AUTHOR, ISBN, and CATEGORY fields to create a
new subset table called BOOKS.
3. Add ITEM NAME to both tables; this field will relate each subset table
to the data table.
4. Compose a suitable description for both subset tables and add
them to the final table list. Indicate each table’s type as “Subset.”
Figure 7.29 shows the new subset table structures.
Take a moment to review your table structures once more. You may dis-
cover that you’ve created subset tables without knowing it. Tables that
have almost identical structures are commonly subset tables; there are
usually only a few unique fields that distinguish one table from the
other. For example, consider the two partial table structures in
Figure 7.30. Each table represents a distinct aspect of the same subject.
Both of these tables represent employees, but each represents a specific
type of employee. Notice, however, that there are generic fields common
From the Library of Stephen Benoit
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238 Chapter 7 Establishing Table Structures
Figure 7.29. The new subset table structures.
Table Structures
Manufacturer
Model
Warranty Expiration Date
Item Name
Equipment
Publisher
Author
ISBN
Category
Item Name
BooksInventory
Item Name
Item Description
Current Value
Insured Value
Date Entered
Figure 7.30. Previously unidentified subset tables.
Table StructuresTable Structures
FTELast Name
FTEDate Hired
Salary Amount
Position
FTEFirst Name
Full-Time Employees
FTEStreet Address
FTECity
FTEState
PTELast Name
PTEDate Hired
Hourly Rate
PTEFirst Name
Part-Time Employees
Skill Level
PTEStreet Address
PTECity
PTEState
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Case Study 239
to both tables: first name, last name, date hired, street address, city,
and state. These fields are duplicated unnecessarily, so you’ll need to
refine the table structures to resolve this problem.
Refining Previously Unidentified Subset Tables
When you identify subset tables such as these, you can refine them us-
ing these steps:
1. Remove all the fields that the subset tables have in common and
use them as the basis for a new data table.
2. Identify what subject the new data table represents, and then give
the table an appropriate name.
3. Make sure that the subset tables represent subordinate subjects of
the data table and modify the subset table names as necessary.
4. Compose a suitable description for the data table and then add it
to the final table list. Indicate the table type as “Data.”
Figure 7.31 shows the results of using these steps on the FULL-TIME
EMPLOYEES and PART-TIME EMPLOYEES tables.
At this point, all of your table structures should be in pretty good shape.
You will need to refine them even further, however, as you learn about
primary keys, foreign keys, relationships, and business rules.
You’re now going to define the preliminary table list for Mike’s Bikes. As
you know, the first thing you need to do is review the preliminary field
list to determine what subjects you can infer from the fields on the list.
Figure 7.32 shows a partial sample of that list.
CASE STUDY
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240 Chapter 7 Establishing Table Structures
After carefully reviewing the entire preliminary field list, you determine
that the fields on the list suggest these subjects: customers, employees,
invoices, products, and vendors. You then compile these items into the
first version of your preliminary table list.
Figure 7.31. The results of refining the subset tables.
Table Structures
EmpLast Name
Date Hired
EmpFirst Name
Employees
EmpStreet Address
EmpCity
EmpState
EmpLast Name
Salary Amount
Position
EmpFirst Name
Full-Time Employees
EmpLast Name
Hourly Rate
EmpFirst Name
Part-Time Employees
Skill Level
Figure 7.32. The preliminary field list for Mike’s Bikes.
Preliminary Field List as of 07/05/96
Office PhoneBirth Date
Unit PriceEmployee City
CategoryEmployee Address
Product NameEmployee Name
Invoice NumberCustomer Name
Invoice DateCustomer Address
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Case Study 241
Now you create a second version of the list by merging the current pre-
liminary table list with the list of subjects you created during the analy-
sis process. Keep the following steps in mind as you merge the two lists
together:
1. Resolve items that are duplicated on both lists. Remember that a
single item can appear on both lists yet represent different sub-
jects. When you identify such items, use the appropriate
techniques to resolve this problem.
2. Resolve items that represent the same subject but have different
names. You want to ensure that only one table represents a partic-
ular subject.
3. Combine the remaining items together into one list. The combined
list becomes the second version of the preliminary table list.
After following these steps, your preliminary table list should look simi-
lar to the one shown in Figure 7.33.
You cross out “Customers,” “Employees,” and “Products” on the list of
subjects because they represent the same subjects as their counterparts
Figure 7.33. The second version of the preliminary table list.
Preliminary Table ListList of Subjects
Customers
Products
Sales
Suppliers
Employees
Customers
Products
Employees
Invoices
Vendors
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242 Chapter 7 Establishing Table Structures
on the preliminary table list. The SALES table has no counterpart on
the preliminary table list, but it does represent the same subject as “In-
voices.” “Invoices” is most meaningful to Mike and his staff, however, so
you use it on the preliminary table list instead of “Sales.” A similar situ-
ation exists between “Suppliers” and “Vendors”; Mike selects “Vendors”
as the name to appear on the preliminary table list, so you cross out
“Suppliers.”
Now you’ll work toward the final version of the preliminary table list.
Use the mission objectives you created at the beginning of the database-
design process to determine whether there are subjects you may have
overlooked during the previous two procedures. Identify each subject
represented in the mission objectives using the subject-identification
technique. Once you’ve identified as many subjects as possible, you can
use the steps from the second procedure to crosscheck these subjects
against the subjects currently listed on the preliminary table list. When
you’ve completed the review and have resolved any duplicate items,
your final version of the preliminary table list is complete.
As it turns out, all of the subjects you’ve identified from the mission ob-
jectives for Mike’s Bikes already appear on the preliminary table list.
This is good news because it allows you to complete your crosscheck
quite easily. Satisfied that you’ve completed the task thoroughly, you
now have the final version of the preliminary table list.
Now that the preliminary table list is complete, you’re ready to trans-
form it into a final table list. Keep these steps in mind as you begin this
process:
❖ Note Selecting a name that best represents the subject of the table is an arbitrary task. A good rule to follow is to use the name
that is most meaningful to everyone in the organization.
From the Library of Stephen Benoit
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Case Study 243
1. Refine the table names. Use the appropriate guidelines to ensure
that each table name is clear, unambiguous, descriptive, and
meaningful.
2. Compose a suitable description for each table. Make certain that
the table description explicitly defines the table and states its
importance to the organization. Use the pertinent guidelines to
create each table description.
3. Indicate the table’s type. Remember that a table can be classified
in one of four ways—data, linking, subset, or validation. At this
point, all of your tables are data tables.
Figure 7.34 shows a partial example of the final table list for Mike’s
Bikes.
The next order of business is to associate fields from the preliminary
field list with each table in the final table list. Make certain you select
Figure 7.34. A partial listing of the final table list for Mike’s Bikes.
Final Table List
Employees
Customers
Name
Data
Data
Type
The people who purchase the products we have to offer. Keeping track of our customers allows us to promote our business and obtain valuable feedback in assessing the quality of our customer service.
Description
The people who work for our company in various capacities. This information is important for tax purposes, health benefits, and work-related issues.
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the fields that best represent characteristics of each table’s subject;
each field should define or describe a particular aspect of the subject.
Figure 7.35 shows a partial example of the table structures for Mike’s
Bikes.
Now you refine the fields. Remember to follow these steps as you work
with each field:
1. Improve the field name. Use the appropriate guidelines to ensure
that each field name is as clear, unambiguous, and descriptive as
possible.
2. Determine whether the field complies with the Elements of the Ideal
Field. Make certain you check for multipart and multivalued
fields. As you learned earlier, they can cause a number of prob-
lems within a table.
As you review the fields, you decide to abbreviate some of the field
names in the CUSTOMERS, EMPLOYEES, and INVOICES tables, short-
Figure 7.35. A partial listing of the table structures for Mike’s Bikes.
Table Structures
EmployeesCustomers Invoices Products
Employee NameCustomer First Name Invoice Number Product Name
Date HiredStatus Customer First Name Retail Price
Employee AddressCustomer Last Name Invoice Date Product Description
Employee PhoneCustomer Phone Employee Name Category
SSNCustomer Address Customer Last Name Wholesale Price
Position Customer Phone Quantity
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ening CUSTOMER to CUST and EMPLOYEE to EMP. You also decide that
the field name QUANTITY (in the PRODUCTS table) does not completely
describe the characteristic it represents, so you change it to QUANTITY ON
HAND. The phone fields in the CUSTOMERS and EMPLOYEES tables
suffer the same problem, so you change them to CUSTHOME PHONE and
EMPHOME PHONE respectively. Furthermore, you change SSN to SOCIAL SE-
CURITY NUMBER so that the field name is absolutely unambiguous.
Further investigation of the fields reveals that almost all of them comply
with the Elements of the Ideal Field. The only exceptions are the ad-
dress fields in the CUSTOMERS and EMPLOYEES tables, and the EM-
PLOYEE NAME fields in the EMPLOYEES and INVOICES tables. After
ascertaining that you can decompose each address field into four indi-
vidual items—street address, city, state, and zip code—you transform
these items into fields and add them to the CUSTOMERS and EMPLOY-
EES tables. Similarly, you notice that the EMPLOYEE NAME field represents
two items—first name and last name—and you make the appropriate
adjustments to that field in the EMPLOYEES and INVOICES tables.
Figure 7.36 shows the result of all the changes you’ve made to the fields.
Your final task is to refine the table structures. Make certain that you
have assigned the appropriate fields to each table and that you have
properly defined each table. Remember to follow these steps as you
work with each table:
1. Resolve unnecessary duplicate fields. When you create new tables
as a result of resolving duplicate fields, make sure you properly
identify them and add them to the final table list.
2. Determine whether each table complies with the Elements of the
Ideal Table. Make certain you resolve all the anomalies you identify
in the fields or within the table structure as a whole.
3. Establish subset tables as appropriate. Make certain you properly
identify these tables and add them to the final table list as well.
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As you complete your review of the tables, you determine that all of them
conform to the Elements of the Ideal Table with the exception of the IN-
VOICES table. The only problem with this table is that it contains an un-
necessary duplicate field: CUSTHOME PHONE. You can remove this field
from the table, however, because it provides only reference information.
As you work with the PRODUCTS table, you notice that there are fields
you might be able to remove and then use as the basis for a subset ta-
ble. So you review the table once again. Figure 7.37 shows the PROD-
UCTS table structure you’re currently examining. (This is an expanded
version of the table structure shown in Figure 7.36.)
Your assumption proves correct. You determine that certain fields de-
scribe a service, and you can construe a service as being a different
type of product. A service is similar to a product in that it has a name,
description, and category, but it is different inasmuch as it has a type,
materials charge, and service charge. With this in mind, you create a
Figure 7.36. Refinements to the fields in the table structures.
Table Structures
ProductsCustomers Employees Invoices
Product NameCustFirst Name EmpFirst Name Invoice Number
Product DescriptionCustLast Name EmpLast Name Invoice Date
CategoryCustHome Phone EmpHome Phone EmpFirst Name
Wholesale PriceCustStreet Address Social Security Number EmpLast Name
Retail PriceCustCity EmpStreet Address CustFirst Name
Quantity On HandCustState EmpCity CustLast Name
CustZipcode EmpState CustHome Phone
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new subset table called SERVICES, make the appropriate modifications
to the PRODUCTS table, and use the PRODUCT NAME field to relate the
two tables to each other. You then add the suitable listing for the SER-
VICES table to the final table list. Figure 7.38 shows the revised PROD-
UCTS table and the new SERVICES subset table.
Figure 7.37. The PRODUCTS table structure (expanded version).
Table Structures
Products
Product Name Service Name
Quantity On Hand Service Charge
Product Description Service Description
Wholesale Price Service Type
Retail Price Materials Charge
Category Service Category
Figure 7.38. The new PRODUCTS and SERVICES tables.
Table Structures
ServicesProducts
Product NameProduct Name
Retail Price
Service TypeProduct Description
Materials ChargeCategory
Service ChargeWholesale Price
Quantity On Hand
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Summary
We opened the chapter with a discussion of the preliminary table list.
This list constitutes the initial table structures for the new database.
You learned how to develop this list using the preliminary field list, the
list of subjects, and the mission objectives, all of which you compiled
during the analysis phase of the database-design process.
Next we discussed the procedure for transforming the preliminary table
list into a final table list, which contains the name, type, and description
of each table in the database. You learned a set of guidelines for creating
table names, and another set of guidelines for composing table descrip-
tions. We then worked on creating table names that are unambiguous,
descriptive, and meaningful and descriptions that explicitly define ta-
bles, as well as stating their importance to the organization. You also
learned that enlisting the help of users and management is crucial to the
process of developing well-defined table descriptions. Table descriptions
must be suitable and easily understood by everyone in the organization.
We then discussed the process of associating fields with each table on
the final table list. Here you learned how to build a structure for a given
table using fields from the preliminary field list that best represent
characteristics of the table’s subject.
Refining fields was the next subject of discussion, and you learned a set
of guidelines for creating field names that will help you ensure that they
are clear, descriptive, and meaningful. You also learned about the Ele-
ments of the Ideal Field. Now you know that you can resolve anomalies
in a field by determining whether it complies with these elements. We
then discussed how to resolve multipart and multivalued fields. You
learned that decomposing multipart fields yields new fields, whereas de-
composing multivalued fields yields new tables.
The chapter closes with a discussion of refining table structures. You
learned to identify the Elements of the Ideal Table, and you now know
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Review Questions 249
that you can ferret out a problem in table structure by determining
whether a table complies with these elements. We then discussed un-
necessary duplicate fields, and you now know that they appear in a ta-
ble for two reasons: to supply reference information or to represent
different occurrences of the same type of value. You then learned how to
resolve duplicate fields to eliminate the problems they present.
The final discussion centered on the topic of subset tables. As you now
know, a subset table represents a subordinate subject of a particular
data table, and there is a distinct relationship between the subset table
and the data table. You also know that you can explicitly create subset
tables. You then learned that you may have unknowingly created subset
tables earlier in the database-design process and that you need to look
for subset tables you have not previously identified. When you identify a
subset table, you refine it and add it to the final table list.
Review Questions
1. How do you identify and establish tables for the new database?
2. Why do you use the preliminary field list to help you define tables
for the database?
3. What action do you take when an item on the list of subjects and a
differently named item on the preliminary table list both represent
the same subject?
4. What information does the final table list provide?
5. State three guidelines for creating table names.
6. State two guidelines for composing table descriptions.
7. How do you assign fields to a table on the final table list?
8. State three guidelines for creating field names.
9. What two problems can poorly designed fields cause?
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10. What can you use to resolve field anomalies?
11. State three of the Elements of the Ideal Field.
12. Under what condition is redundant data acceptable?
13. In general terms, what three steps do you follow to resolve a multi-
valued field?
14. When is it necessary to use a duplicate field in a table?
15. How can you refine table structures?
16. State three of the Elements of the Ideal Table.
17. What is a subset table?
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8 Keys
A fact in itself is nothing. It is valuable only for the idea attached to it, or for the proof which it furnishes.
—CLAUDE BERNARD
Topics Covered in This Chapter
Why Keys Are Important
Establishing Keys for Each Table
Table-Level Integrity
Reviewing the Initial Table Structures
Case Study
Summary
Review Questions
By now you’ve identified all the subjects that the database will track
and defined the table structures that will represent those subjects. Fur-
thermore, you’ve put the structures through a screening process to con-
trol their makeup and quality. In this next stage of the database-design
process, you’ll begin the task of assigning keys to each table. You’ll soon
learn that there are different types of keys, and each plays a particular
role within the database structure. All but one key is assigned during
this stage; you’ll assign the remaining key later (in Chapter 10) as you
establish relationships between tables.
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Why Keys Are Important
Keys are crucial to a table structure for the following reasons:
• They ensure that each record in a table is precisely identified. As
you already know, a table represents a singular collection of simi-
lar objects or events. (For example, a CLASSES table represents a
collection of classes, not just a single class.) The complete set of
records within the table constitutes the collection, and each
record represents a unique instance of the table’s subject within
that collection. You must have some means of accurately identify-
ing each instance, and a key is the device that allows you to do so.
• They help establish and enforce various types of integrity. Keys are
a major component of table-level integrity and relationship-level
integrity. For instance, they enable you to ensure that a table has
unique records and that the fields you use to establish a relation-
ship between a pair of tables always contain matching values.
• They serve to establish table relationships. As you’ll learn in Chap-
ter 10, you’ll use keys to establish a relationship between a pair of
tables.
Always make certain that you define the appropriate keys for each table.
Doing so will help you guarantee that the table structures are sound,
that redundant data within each table is minimal, and that the relation-
ships between tables are solid.
Establishing Keys for Each Table
Your next task is to establish keys for each table in the database. There
are four main types of keys: candidate, primary, foreign, and non-keys.
A key’s type determines its function within the table.
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Establishing Keys for Each Table 253
Candidate Keys
The first type of key you establish for a table is the candidate key, which
is a field or set of fields that uniquely identifies a single instance of the
table’s subject. Each table must have at least one candidate key. You’ll
eventually examine the table’s pool of available candidate keys and des-
ignate one of them as the official primary key for the table.
Before you can designate a field as a candidate key, you must make cer-
tain it complies with all of the Elements of a Candidate Key. These ele-
ments constitute a set of guidelines you can use to determine whether
the field is fit to serve as a candidate key. You cannot designate a field
as a candidate key if it fails to conform to any of these elements.
Elements of a Candidate Key
• It cannot be a multipart field. You’ve seen the problems with multi-
part fields, so you know that using one as an identifier is a bad
idea.
• It must contain unique values. This element helps you guard
against duplicating a given record within the table. Duplicate
records are just as bad as duplicate fields, and you must avoid
them at all costs.
• It cannot contain null values. As you already know, a null value
represents the absence of a value. There’s absolutely no way a
candidate key field can identify a given record if its value is null.
• Its value cannot cause a breach of the organization’s security or pri-
vacy rules. Values such as passwords and Social Security Num-
bers are not suitable for use as a candidate key.
• Its value is not optional in whole or in part. A value that is optional
implies that it may be null at some point. You can infer, then, that
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254 Chapter 8 Keys
an optional value automatically violates the previous element and
is, therefore, unacceptable. (This caveat is especially applicable
when you want to use two or more fields as a candidate key.)
• It comprises a minimum number of fields necessary to define
uniqueness. You can use a combination of fields (treated as a
single unit) to serve as a candidate key, so long as each field
contributes to defining a unique value. Try to use as few fields as
possible, however, because overly complex candidate keys can
ultimately prove to be difficult to work with and difficult to
understand.
• Its values must uniquely and exclusively identify each record in the
table. This element helps you guard against duplicate records and
ensures that you can accurately reference any of the table’s
records from other tables in the database.
• Its value must exclusively identify the value of each field within a
given record. This element ensures that the table’s candidate keys
provide the only means of identifying each field value within the
record. (You’ll learn more about this particular element in the sec-
tion on primary keys.)
• Its value can be modified only in rare or extreme cases. You should
never change the value of a candidate key unless you have an
absolute and compelling reason to do so. A field is likely to have
difficulty conforming to the previous elements if you can change
its value arbitrarily.
Establishing a candidate key for a table is quite simple: Look for a field
or set of fields that conforms to all of the Elements of a Candidate Key.
You’ll probably be able to define more than one candidate key for a given
table. Loading a table with sample data will give you the means to iden-
tify potential candidate keys accurately. (You used this same technique
in the previous chapter.)
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Establishing Keys for Each Table 255
See if you can identify any candidate keys for the table in Figure 8.1.
You probably identified EMPLOYEE ID, SOCIAL SECURITY NUMBER, EMPLAST
NAME, EMPFIRST NAME and EMPLAST NAME, EMPZIPCODE, and EMPHOME PHONE
as potential candidate keys. But you’ll need to examine these fields
more closely to determine which ones are truly eligible to become candi-
date keys. Remember that you must automatically disregard any field(s)
failing to conform to even one of the Elements of a Candidate Key.
Upon close examination, you can draw the following conclusions:
• EMPLOYEE ID is eligible. This field conforms to every element of a
candidate key.
• SOCIAL SECURITY NUMBER is ineligible because it could contain null val-
ues and will most likely compromise the organization’s privacy
rules. Contrary to what the sample data shows, this field could
contain a null value. For example, there are many people working
in the United States who do not have Social Security numbers be-
cause they are citizens of other countries.
Figure 8.1. Are there any candidate keys in this table?
Employees
EmpFirst Name
Kendra
Timothy
Shannon
Estela
Susan
Katherine
Timothy
Social Security Number
856-91-9938
901-48-0039
816-93-1299
955-92-5583
978-02-1129
886-11-2231
801-22-1734
EmpLast Name
Bonnicksen
Ennis
McLain
Pundt
McLain
Erlich
Sherman
EmpStreet Address
1204 Bryant Road
7402 Kingman Drive
4141 Lake City Way
101 C Street, Apt. 32
2100 Mineola Avenue
101 C Street, Apt. 32
66 NE 120th
EmpCity
Seattle
Redmond
Seattle
Bellevue
Seattle
Bellevue
Bothell
EmpState
WA
WA
WA
WA
WA
WA
WA
EmpZipcode
98157
98115
98136
98046
98115
98046
98216
EmpHome Phone
363-9948
527-4992
336-5992
322-6992
572-9948
322-6992
522-3232
Employee ID
1000
1002
1003
1005
1004
1001
1006
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• EMPLAST NAME is ineligible because it can contain duplicate values.
As you’ve learned, the values of a candidate key must be unique.
In this case there can be more than one occurrence of a particular
last name.
• EMPFIRST NAME and EMPLAST NAME are eligible. The combined values
of both fields will supply a unique identifier for a given record. Al-
though multiple occurrences of a particular first name or last
name will occur, the combination of a given first name and last
name will always be unique. (Some of you are probably saying,
“This is not necessarily always true.” You’re absolutely right.
Don’t worry; we’ll address this issue shortly.)
• EMPZIPCODE is ineligible because it can contain duplicate values.
Many people live in the same zip code area, so the values in
EMPZIPCODE cannot possibly be unique.
• EMPHOME PHONE is ineligible because it can contain duplicate values
and is subject to change. This field will contain duplicate values
for either of these reasons:
1. One or more family members work for the organization.
2. One or more people share a residence that contains a single
phone line.
❖ Note Despite its widespread use in many types of databases, I would strongly recommend that you refrain from using SOCIAL SE-
CURITY NUMBER as a candidate key (or a primary key, for that mat-
ter) in any of your database structures. In many instances, it
doesn’t conform to the Elements of a Candidate Key. You can
learn some very interesting facts about Social Security numbers
(which will shed some light on why they make poor candidate/pri-
mary keys) by visiting the Social Security Adminstration’s Web
site at http://www.ssa.gov.
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Establishing Keys for Each Table 257
You can confidently state that the EMPLOYEES table has two candidate
keys: EMPLOYEE ID and the combination of EMPFIRST NAME and EMPLAST
NAME.
Mark candidate keys in your table structures by writing the letters “CK”
next to the name of each field you designate as a candidate key. A can-
didate key composed of two or more fields is known as a composite can-
didate key, and you’ll write “CCK” next to the names of the fields that
make up the key. When you have two or more composite candidate
keys, use a number within the mark to distinguish one from another. If
you had two composite candidate keys, for example, you would mark
one as “CCK1” and the other as “CCK2.”
Apply this technique to the candidate keys for the EMPLOYEES table in
Figure 8.1. Figure 8.2 shows how your structure should look when
you’ve completed this task.
Figure 8.2. Marking candidate keys in the EMPLOYEES table structure.
Table Structures
Employees
EmpLast Name CCK
EmpStreet Address
EmpCity
EmpZipcode
EmpHome Phone
Employee ID CK
EmpState
EmpFirst Name CCK
Social Security Number
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Now, try to identify as many candidate keys as you can for the PARTS
table in Figure 8.3.
At first glance, you may believe that PART NAME, MODEL NUMBER, the com-
bination of PART NAME and MODEL NUMBER, and the combination of MANU-
FACTURER and PART NAME are potential candidate keys. After investigating
this theory, however, you come up with the following results:
• PART NAME is ineligible because it can contain duplicate values. A
given part name will be duplicated when the part is manufactured
in several models. For example, this is the case with Faust Brake
Levers.
• MODEL NUMBER is ineligible because it can contain null values. A can-
didate key value must exist for each record in the table. As you
can see, some parts do not have a model number.
• PART NAME and MODEL NUMBER are ineligible because either field can
contain null values. The simple fact that MODEL NUMBER can con-
tain null values instantly disqualifies this combination of fields.
• MANUFACTURER and PART NAME are ineligible because the values for
these fields seem to be optional. Recall that a candidate key value
Figure 8.3. Can you identify any candidate keys in the PARTS table?
Parts
Part Name
Shimka XT Cranks
Faust Brake Levers
MiniMite Pump
Hobo Fanny Pack
Diablo Bike Pedals
Shimka Truing Stand
Faust Brake Levers
Model Number
XT-113
BL / 45
Mtn-A26
SP-100
BL / 60
Manufacturer Name
Shimka Incorporated
Faust USA
MiniMite
Hobo Bike Company
Diablo Sports
Faust USA
Retail Price
199.95
53.79
35.00
59.00
129.50
37.95
79.95
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Establishing Keys for Each Table 259
cannot be optional in whole or in part. In this instance, you can
infer that entering the manufacturer name is optional when it
appears as a component of the part name; therefore, you cannot
designate this combination of fields as a candidate key.
It’s evident that you don’t have a single field or set of fields that quali-
fies as a candidate key for the PARTS table. This is a problem because
each table must have at least one candidate key. Fortunately, there is
a solution.
Artificial Candidate Keys
When you determine that a table does not contain a candidate key, you
can create and use an artificial (or surrogate) candidate key. (It’s artifi-
cial in the sense that it didn’t occur “naturally” in the table; you have to
manufacture it.) You establish an artificial candidate key by creating a
new field that conforms to all of the Elements of a Candidate Key and
then adding it to the table; this field becomes the official candidate key.
You can now solve the problem in the PARTS table. Create an artificial
candidate key called PART NUMBER and assign it to the table. (The new
field will automatically conform to the Elements of a Candidate Key be-
cause you’re creating it from scratch.) Figure 8.4 shows the revised
structure of the PARTS table.
When you’ve established an artificial candidate key for a table, mark the
field name with a “CK” in the table structure, just as you did for the EM-
PLOYEES table in the previous example.
You may also choose to create an artificial candidate key when it would
be a stronger (and thus, more appropriate) candidate key than any of
the existing candidate keys. Assume you’re working on an EMPLOYEES
table and you determine that the only available candidate key is the
combination of the EMPFIRST NAME and EMPLAST NAME fields. Although this
may be a valid candidate key, using a single-field candidate key might
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260 Chapter 8 Keys
prove more efficient and may identify the subject of the table more eas-
ily. Let’s say that everyone in the organization is accustomed to using a
unique identification number rather than a name as a means of identi-
fying an employee. In this instance, you can choose to create a new field
named EMPLOYEE ID and use it as an artificial candidate key. This is an
absolutely acceptable practice—do this without hesitation or reserva-
tion if you believe it’s appropriate.
Review the candidate keys you’ve selected and make absolutely certain
that they thoroughly comply with the Elements of a Candidate Key.
Don’t be surprised if you discover that one of them is not a candidate
key after all—incorrectly identifying a field as a candidate key happens
❖ Note I commonly create an ID field (such as EMPLOYEE ID, VEN- DOR ID, DEPARTMENT ID, CATEGORY ID, and so on) and use it as an ar-
tificial candidate key. It always conforms to the Elements of a
Candidate Key, makes a great primary key (eventually), and, as
you’ll see in Chapter 10, makes the process of establishing table
relationships much easier.
Figure 8.4. The PARTS table with the artificial candidate key PART NUMBER.
Parts
Part Number
41000
41001
41002
41003
41004
41005
41006
Part Name
Shimka XT Cranks
Faust Brake Levers
MiniMite Pump
Hobo Fanny Pack
Diablo Bike Pedals
Shimka Truing Stand
Faust Brake Levers
Model Number
XT-113
BL / 45
Mtn-A26
SP-100
BL / 60
Manufacturer Name
Shimka Incorporated
Faust USA
MiniMite
Hobo Bike Company
Diablo Sports
Faust USA
Retail Price
199.95
53.79
35.00
59.00
129.50
37.95
79.95
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Establishing Keys for Each Table 261
occasionally. When this does occur, just remove the “CK” designator
from the field name in the table structure. Deleting a candidate key
won’t pose a problem as long as the table has more than one candidate
key. If you discover, however, that the only candidate key you identified
for the table is not a candidate key, you must establish an artificial can-
didate key for the table. After you’ve defined the new candidate key, re-
member to mark its name with a “CK” in the table structure.
Primary Keys
By now, you’ve established all the candidate keys that seem appropriate
for every table. Your next task is to establish a primary key for each ta-
ble, which is the most important key of all.
• A primary key field exclusively identifies the table throughout the
database structure and helps establish relationships with other
tables. (You’ll learn more about this in Chapter 10.)
• A primary key value uniquely identifies a given record within a
table and exclusively represents that record throughout the entire
database. It also helps to guard against duplicate records.
A primary key must conform to the exact same elements as a candidate
key. This requirement is easy to fulfill because you select a primary key
from a table’s pool of available candidate keys. The process of selecting
a primary key is somewhat similar to that of a presidential election. Ev-
ery four years, several people run for the office of president of the United
States. These individuals are known as “candidates” and they have all of
the qualifications required to become president. A national election is
held, and a single individual from the pool of available presidential can-
didates is elected to serve as the country’s official president. Similarly,
you identify each qualified candidate key in the table, run your own
election, and select one of them to become the official primary key of the
table. You’ve already identified the candidates, so now it’s election time!
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Assuming that there is no other marginal preference, here are a couple
of guidelines you can use to select an appropriate primary key:
1. If you have a simple (single-field) candidate key and a composite
candidate key, choose the simple candidate key. It’s always best to
use a candidate key that contains the least number of fields.
2. Choose a candidate key that incorporates part of the table name
within its own name. For example, a candidate key with a name
such as SALES INVOICE NUMBER is a good choice for the SALES
INVOICES table.
Examine the candidate keys and choose one to serve as the primary key
for the table. The choice is largely arbitrary—you can choose the one
that you believe most accurately identifies the table’s subject or the one
that is the most meaningful to everyone in the organization. For exam-
ple, consider the EMPLOYEES table again in Figure 8.5.
Either of the candidate keys you identified within the table could serve
as the primary key. You might decide to choose EMPLOYEE ID if everyone
in the organization is accustomed to using this number as a means of
identifying employees in items such as tax forms and employee benefits
programs. The candidate key you ultimately choose becomes the pri-
mary key of the table and is governed by the Elements of a Primary Key.
These elements are exactly the same as those for the candidate key, and
you should enforce them to the letter. For the sake of clarity, here are
the Elements of a Primary Key:
Elements of a Primary Key
• It cannot be a multipart field.
• It must contain unique values.
• It cannot contain null values.
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Establishing Keys for Each Table 263
• Its value cannot cause a breach of the organization’s security or
privacy rules.
• Its value is not optional in whole or in part.
• It comprises a minimum number of fields necessary to define
uniqueness.
• Its values must uniquely and exclusively identify each record in
the table.
• Its value must exclusively identify the value of each field within a
given record.
• Its value can be modified only in rare or extreme cases.
Figure 8.5. Which candidate key should become the primary key of the EMPLOYEES table?
Table Structures
Employees
EmpLast Name CCK
EmpStreet Address
EmpCity
EmpZipcode
EmpHome Phone
Employee ID CK
EmpState
EmpFirst Name CCK
Social Security Number
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Before you finalize your selection of a primary key, it is imperative that
you make absolutely certain that the primary key fully complies with
this particular element:
• Its value must exclusively identify the value of each field within a
given record.
Each field value in a given record should be unique throughout the en-
tire database (unless it is participating in establishing a relationship be-
tween a pair of tables) and should have only one exclusive means of
identification—the specific primary key value for that record.
You can determine whether a primary key fully complies with this ele-
ment by following these steps:
1. Load the table with sample data.
2. Select a record for test purposes and note the current primary key
value.
3. Examine the value of the first field (the one immediately after the
primary key) and ask yourself this question:
Does this primary key value exclusively identify the current
value of <fieldname>?
a. If the answer is yes, move to the next field and repeat the
question.
b. If the answer is no, remove the field from the table, move to the
next field and repeat the question.
4. Continue this procedure until you’ve examined every field value in
the record.
A field value that the primary key does not exclusively identify indicates
that the field itself is unnecessary to the table’s structure; therefore, you
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Establishing Keys for Each Table 265
should remove the field and reconfirm that the table complies with the
Elements of the Ideal Table. You can then add the field you just removed
to another table structure, if appropriate, or you can discard it com-
pletely because it is truly unnecessary.
Here’s an example of how you might apply this technique to the partial
table structure in Figure 8.6. (Note that INVOICE NUMBER is the primary
key of the table.)
First, you load the table with sample data. You then select a record for
test purposes—we’ll use the third record for this example—and note the
value of the primary key (13002). Now, pose the question above for each
field value in the record.
Does this primary key value exclusively identify the current
value of . . .
INVOICE DATE? Yes, it does. This invoice number will always iden-
tify the specific date that the invoice was created.
CUSTFIRST NAME? Yes, it does. This invoice number will always iden-
tify the specific first name of the particular cus-
tomer who made this purchase.
Figure 8.6. Does the primary key exclusively identify the value of each field in this table?
Sales Invoices
363-9948
527-4992
336-5992
322-6992
572-9948
322-6992
EmpHome Phone
Pundt
Bonnicksen
Bonnicksen
Pundt
McLain
Erlich
EmpLast Name
Estela
Kendra
Kendra
Estela
Shannon
Katherine
EmpFirst Name
DeSoto
Coie
Cunningham
DeSoto
Coie
Mattson
CustLast Name
Frank
Caroline
David
Frank
Caroline
Gregory
CustFirst Name
06/15/02
06/16/02
06/15/02
06/15/02
06/16/02
06/17/02
Invoice Date
13000
13003
13001
13002
13004
13005
Invoice Number
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CUSTLAST NAME? Yes, it does. This invoice number will always iden-
tify the specific last name of the particular cus-
tomer who made this purchase.
EMPFIRST NAME? Yes, it does. This invoice number will always iden-
tify the specific first name of the particular em-
ployee who served the customer for this sale.
EMPLAST NAME? Yes, it does. This invoice number will always iden-
tify the specific last name of the particular em-
ployee who served the customer for this sale.
EMPHOME PHONE? No, it doesn’t! The invoice number indirectly identi-
fies the employee’s home phone number via the
employee’s name. In fact, it is the current value of
both EMPFIRST NAME and EMPLAST NAME that exclu-
sively identifies the value of EMPHOME PHONE—
change the employee’s name and you must change
the phone number as well. You should now remove
EMPHOME PHONE from the table for two reasons: The
primary key does not exclusively identify its cur-
rent value and (as you’ve probably already ascer-
tained) it is an unnecessary field. As it turns out,
you can discard this field completely because it is
already part of the EMPLOYEES table structure.
After you’ve removed the unnecessary fields you identified during this
test, examine the revised table structure and make sure it complies with
the Elements of the Ideal Table.
The primary key should now exclusively identify the values of the re-
maining fields in the table. This means that the primary key is truly
sound and you can designate it as the official primary key for the table.
Remove the “CK” next to the field name in the table structure and re-
place it with a “PK.” (A primary key composed of two or more fields is
known as a composite primary key, and you mark it with the letters
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Establishing Keys for Each Table 267
“CPK.”) Figure 8.7 shows the revised structure of the SALES INVOICE
table with INVOICE NUMBER as its primary key.
As you create a primary key for each table in the database, keep these
two rules in mind:
Rules for Establishing a Primary Key
1. Each table must have one—and only one—primary key. Because
the primary key must conform to each of the elements that govern
it, only one primary key is necessary for a particular table.
2. Each primary key within the database must be unique—no two
tables should have the same primary key unless one of them is a
subset table. You learned at the beginning of this section that the
primary key exclusively identifies a table throughout the database
structure; therefore, each table must have its own unique primary
Figure 8.7. The revised SALES INVOICES table with its new primary key.
Table Structures
Sales Invoices
CustLast Name
EmpFirst Name
EmpLast Name
Ship Date
Invoice Date
Shipper Name
CustFirst Name
Invoice Number PK
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key in order to avoid any possible confusion or ambiguity concern-
ing the table’s identity. A subset table is excluded from this rule
because it represents a more specific version of a particular data
table’s subject—both tables must share the same primary key.
Later in the database-design process, you’ll learn how to use the pri-
mary key to help establish a relationship between a pair of tables.
Alternate Keys
Now that you’ve selected a candidate key to serve as the primary key for
a particular table, you’ll designate the remaining candidate keys as alter-
nate keys. These keys can be useful to you in an RDBMS program be-
cause they provide an alternative means of uniquely identifying a
particular record within the table. If you choose to use an alternate key
in this manner, mark its name with “AK” or “CAK” (composite alternate
key) in the table structure; otherwise, remove its designation as an alter-
nate key and simply return it to the status of a normal field. You won’t
be concerned with alternate keys for the remainder of the database-
design process, but you will work with them once again as you imple-
ment the database in an RDBMS program. (Implementing and using al-
ternate keys in RDBMS programs is beyond the scope of this work—our
only objective here is to designate them as appropriate. This is in line
with the focus of the book, which is the logical design of a database.)
Figure 8.8 shows the final structure for the EMPLOYEES table with the
proper designation for both the primary key and the alternate keys.
Non-keys
A non-key is a field that does not serve as a candidate, primary, alter-
nate, or foreign key. Its sole purpose is to represent a characteristic of
the table’s subject, and its value is determined by the primary key.
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Table-Level Integrity 269
There is no particular designation for a non-key, so you don’t need to
mark it in the table structure.
Table-Level Integrity
This type of integrity is a major component of overall data integrity, and
it ensures the following:
• There are no duplicate records in a table.
• The primary key exclusively identifies each record in a table.
• Every primary key value is unique.
• Primary key values are not null.
You began establishing table-level integrity when you defined a primary
key for each table and ensured its enforcement by making absolutely
Figure 8.8. The EMPLOYEES table with designated primary and alternate keys.
Table Structures
Employees
EmpLast Name CAK
EmpStreet Address
EmpCity
EmpZipcode
EmpHome Phone
Employee ID PK
EmpState
EmpFirst Name CAK
Social Security Number
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certain that each primary key fully complied with the Elements of a Pri-
mary Key. In the next chapter, you’ll enhance the table’s integrity fur-
ther as you establish field specifications for each field within the table.
Reviewing the Initial Table Structures
Now that the fundamental table definitions are complete, you need to
conduct interviews with users and management to review the work
you’ve done so far. This set of interviews is fairly straightforward and
should be relatively easy to conduct.
During these interviews, you will accomplish these tasks:
• Ensure that the appropriate subjects are represented in the data-
base. Although it’s highly unlikely that an important subject is
missing at this stage of the database-design process, it can hap-
pen. When it does happen, identify the subject, use the proper
techniques to transform it into a table, and develop it to the same
degree as the other tables in the database.
• Make certain that the table names and table descriptions are suit-
able and meaningful to everyone. When a name or description ap-
pears to be confusing or ambiguous to several people in the
organization, work with them to clarify the item as much as possi-
ble. It’s common for some table names and descriptions to im-
prove during the interview process.
• Make certain that the field names are suitable and meaningful to ev-
eryone. Selecting field names typically generates a great deal of dis-
cussion, especially when there is an existing database in place.
You’ll commonly find people who customarily refer to a particular
field by a certain name because “that’s what it’s called on my
screen.” When you change a field name—you have good reasons for
doing so—you must diplomatically explain to these folks that you
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Case Study 271
renamed the field so that it conforms to the standards imposed by
the new database. You can also tell them that the field can appear
with the more familiar name once the database is implemented in
an RDBMS program. What you’ve said is true; many RDBMSs al-
low you to use one name for the field’s physical definition and an-
other name for display purposes. This feature, however, does not
change, reduce, or negate the need for you to follow the guidelines
for creating field names that you learned in Chapter 7.
• Verify that all the appropriate fields are assigned to each table.
This is your best opportunity to make certain that all of the neces-
sary characteristics pertaining to the subject of the table are in
place. You’ll commonly discover that you accidentally overlooked
one or two characteristics earlier in the design process. When this
happens, identify the characteristics, use the appropriate tech-
niques to transform them into fields, and follow all the necessary
steps to add them to the table.
When you’ve completed the interviews, you’ll move to the next phase of
the database-design process and establish field specifications for every
field in the database.
It’s now time to establish keys for each table in the Mike’s Bikes data-
base. As you know, your first order of business is to establish candidate
keys for each table. Let’s say you decide to start with the CUSTOMERS
table in Figure 8.9.
As you review each field, you try to determine whether it conforms to
the Elements of a Candidate Key. You determine that STATUS, CUSTHOME
PHONE, and the combination of CUSTFIRST NAME and CUSTLAST NAME are
potential candidate keys, but you’re not quite certain whether any of
CASE STUDY
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272 Chapter 8 Keys
them will completely conform to all of the elements. So you decide to test
the keys by loading the table with sample data as shown in Figure 8.10.
Always remember that a field must comply with all of the Elements of a
Candidate Key in order to qualify as a candidate key. You must immedi-
ately disqualify the field if it does not fulfill this requirement.
Figure 8.9. The CUSTOMERS table structure in the Mike’s Bikes database.
Table Structures
Customers
CustStreet Address
CustCity
CustState
CustZipcode
Status
CustFirst Name
CustHome Phone
CustLast Name
Figure 8.10. Testing candidate keys in the CUSTOMERS table.
Customers
CustHome Phone
422-4982
363-9360
363-9360
365-7199
441-3987
322-1178
332-0499
Status
Valued
Valued
Preferred
Valued
Preferred
CustZipcode
98004
98225
98225
98115
98001
98126
98026
CustState
WA
WA
WA
WA
WA
WA
WA
CustCity
Bellevue
Redmond
Redmond
Seattle
Bothell
Kent
Seattle
CustStreet Address
2121 NE 35th
7525 Taxco Lane
7525 Taxco Lane
301 N Main
750 Pike Street
101 9th Avenue
115 Pine Place
CustLast Name
Berlin
Brigan
Carmichael
Chavez
Chavez
Bradley
Cooper
CustFirst Name
Bridget
Kel
Barbara
Daniel
Daniel
Phillip
Sandi
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Case Study 273
As you examine the table, you draw these conclusions:
• STATUS is ineligible because it will probably contain duplicate values.
As business grows, Mike is going to have many “Valued” customers.
• CUSTHOME PHONE is ineligible because it will probably contain dupli-
cate values. The sample data reveals that two customers can live
in the same residence and have the same phone number.
• CUSTFIRST NAME and CUSTLAST NAME are ineligible because they will
probably contain duplicate values. The sample data reveals that
the combination of first name and last name can represent more
than one distinct customer.
These findings convince you to establish an artificial candidate key for
this table. You then create a field called CUSTOMER ID, confirm that it
complies with the requirements for a candidate key, and add the new
field to the table structure with the appropriate designation.
Figure 8.11 shows the revised structure of the CUSTOMERS table.
Figure 8.11. The CUSTOMERS table with the new artificial candidate key, CUSTOMER ID.
Table Structures
Customers
CustStreet Address
CustCity
CustState
CustZipcode
Status
CustFirst Name
CustHome Phone
CustLast Name
Customer ID CK
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Now you’ll repeat this procedure for each table in the database. Remem-
ber to make certain that every table has at least one candidate key.
The next order of business is to establish a primary key for each table.
As you know, you select the primary key for a particular table from the
table’s pool of available candidate keys. Here are a few points to keep in
mind when you’re choosing a primary key for a table with more than
one candidate key:
• Choose a simple (single-field) candidate key over a composite can-
didate key.
• If possible, pick a candidate key that has the table name incorpo-
rated into its own name.
• Select the candidate key that best identifies the subject of the
table or is most meaningful to everyone in the organization.
You begin by working with the EMPLOYEES table in Figure 8.12. As you
review the candidate keys, you decide that EMPLOYEE NUMBER is a much
better choice for a primary key than the combination of EMPFIRST NAME
and EMPLAST NAME because Mike’s employees are already accustomed to
identifying themselves by their assigned numbers. Using EMPLOYEE NUM-
BER makes perfect sense, so you select it as the primary key for the table.
Now you perform one final task before you designate EMPLOYEE NUMBER
as the official primary key of the table: You make absolutely certain that
it exclusively identifies the value of each field within a given record. So,
you test EMPLOYEE NUMBER by following these steps:
1. Load the EMPLOYEES table with sample data.
2. Select a record for test purposes and note the current value of
EMPLOYEE NUMBER.
3. Examine the value of the first field (the one immediately after
EMPLOYEE NUMBER) and ask yourself this question:
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Case Study 275
Does this primary key value exclusively identify the current
value of <fieldname>?
a. If the answer is yes, move to the next field and repeat the
question.
b. If the answer is no, remove the field from the table, move to the
next field and repeat the question. (Be sure to determine
whether you can add the field you just removed to another
table structure, if appropriate, or discard it completely because
it is truly unnecessary.)
4. Continue this procedure until you’ve examined every field value in
the record.
You know that you’ll have to remove any field containing a value that
EMPLOYEE NUMBER does not exclusively identify. EMPLOYEE NUMBER does ex-
clusively identify the value of each field in the test record, however, so
Figure 8.12. The EMPLOYEES table structure in the Mike’s Bikes database.
Table Structures
Employees
EmpLast Name CCK
EmpStreet Address
EmpCity
EmpZipcode
EmpHome Phone
Employee Number CK
EmpState
EmpFirst Name CCK
Social Security Number
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you use it as the official primary key for the EMPLOYEES table and
mark its name with the letters “PK” in the table structure. You then re-
peat this process with the rest of the tables in Mike’s new database until
every table has a primary key.
Remember to keep these rules in mind as you establish primary keys for
each table:
• Each table must have one—and only one—primary key.
• Each primary key within the database should be unique—no two
tables should have the same primary key (unless one of them is a
subset table).
As you work through the tables in Mike’s database, you remember that
the SERVICES table is a subset table. You created it during the previous
stage of the design process (in Chapter 7), and it represents a more spe-
cific version of the subject represented by the PRODUCTS table. The
PRODUCT NAME field is what currently relates the PRODUCTS table to the
SERVICES subset table. You now know, however, that a subset table
must have the same primary key as the table to which it is related, so
you’ll use PRODUCT NUMBER (the primary key of the PRODUCTS table) as
the primary key of the SERVICES table. Figure 8.13 shows the PROD-
UCTS and SERVICES tables with their primary keys.
The last order of business is to conduct interviews with Mike and his staff
and review all the work you’ve performed on the tables in the database.
As you conduct these interviews, make certain you check the following:
• That the appropriate subjects are represented in the database
• That the table names and descriptions are suitable and meaning-
ful to everyone
• That the field names are suitable and meaningful to everyone
• That all the appropriate fields are assigned to each table
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Summary 277
By the end of the interview, everyone agrees that the tables are in good
form and that all the subjects with which they are concerned are repre-
sented in the database. Only one minor point came up during the dis-
cussions: Mike wants to add a CALL PRIORITY field to the VENDORS table.
There are instances in which more than one vendor supplies a particu-
lar product, and Mike wants to create a way to indicate which vendor he
should call first if that product is unexpectedly out of stock. So, you add
the new field to the VENDORS table and bring the interview to a close.
Summary
The chapter opened with a discussion of the importance of keys. You
learned that there are different types of keys, and each type plays a dif-
ferent role within the database. Each key performs a particular func-
tion, such as uniquely identifying records, establishing various types of
integrity, and establishing relationships between tables. You now know
that you can guarantee sound table structure by making certain that
the appropriate keys are established for each table.
Figure 8.13. Establishing the primary key for the SERVICES subset table.
Table Structures
ServicesProducts
Service TypeProduct Name
Retail Price
Materials ChargeProduct Description
Service ChargeCategory
Wholesale Price
Quantity On Hand
Product Number PKProduct Number PK
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We then discussed the process of establishing keys for each table. We
began by identifying the four main types of keys: candidate, primary,
foreign, and non-keys. First, we looked at the process of establishing
candidate keys for each table. You learned about the Elements of a Can-
didate Key and how to make certain that a field (or set of fields) complies
with these elements. Then you learned that you can create and use an
artificial candidate key when none of the fields in a table can serve as a
candidate key or when a new field would make a stronger candidate key
than any of the existing candidate key fields.
The chapter continued with a discussion of primary keys. You learned
that you select a primary key from a table’s pool of candidate keys and
that the primary key is governed by a set of specific elements. We then
covered a set of guidelines that help you determine which candidate key
to use as a primary key. Next, you learned how to ensure that the cho-
sen primary key exclusively identifies a given record and its set of field
values. When the primary key does not exclusively identify a particular
field value, you know that you must remove the field from the table in
order to ensure the table’s structural integrity. You also know that each
table must have a single, unique primary key.
You then learned that you designate any remaining candidate keys as al-
ternate keys. These keys will be most useful to you when you implement
the database in an RDBMS program because they provide an alternate
means of identifying a given record. We then discussed the non-key field,
which is any field not designated as a candidate, primary, alternate, or
foreign key. You now know that a non-key field represents a characteris-
tic of the table’s subject and that the primary key exclusively identifies
its value.
Table-level integrity was the next subject of discussion, and you learned
that it is established through the use of primary keys and enforced by
the Elements of a Primary Key.
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Review Questions 279
The chapter closed with some guidance on conducting further interviews
with users and management. You now know that these interviews provide
you with a means of reviewing the work you have performed on the tables
and help you to verify and validate the current database structure.
Review Questions
1. State the three reasons why keys are important.
2. What are the four main types of keys?
3. What is the purpose of a candidate key?
4. State four items of the Elements of a Candidate Key.
5. True or False: A candidate key can be composed of more than one
field.
6. Can a table have more than one candidate key?
7. What is an artificial candidate key?
8. What is the most important key you assign to a table?
9. Why is this key important?
10. How do you establish a primary key?
11. State four items of the Elements of a Primary Key.
12. What must you do before you finalize your selection of a primary
key?
13. What is an alternate key?
14. What do you ensure by establishing table-level integrity?
15. Why should you review the initial table structures?
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9 Field Specifications
It has long been an axiom of mine that the little things are infinitely the most important.
—SHERLOCK HOLMES, THE ADVENTURES OF SHERLOCK HOLMES
Topics Covered in This Chapter
Why Field Specifications Are Important
Field-Level Integrity
Anatomy of a Field Specification
Using Unique, Generic, and Replica Field Specifications
Defining Field Specifications for Each Field in the Database
Case Study
Summary
Review Questions
Fields are the bedrock of the database. They represent characteristics of
the subjects that are important to an organization. Fields store the data
that the organization uses as the basis of information—information that
is vital to its daily operations, success, and future growth. Despite their
inherent value, fields are still the most overlooked, underutilized, and
neglected assets of the organization! Frequently, little or no time is spent
ensuring the structural and logical integrity of the fields in the database.
Much is said and written about data integrity, but little is done about
it. Many people believe that keeping an eye on their data-entry person-
nel and having a “foolproof” user interface for the database will greatly
minimize potential data-related problems. This superficial approach to
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data integrity commonly stems from an incorrect belief that proper
data integrity takes too much time to establish. It’s important to note,
however, that the people who don’t have time to establish data integrity
usually spend a large amount of time fixing their improperly designed
databases—typically spending up to three times as long as it would
have taken them to design the database properly in the first place!
In this chapter, you’ll learn how to establish data integrity by defining
field specifications for each field in the database. First, you’ll learn
about the three sets of elements that compose a field specification; then
you’ll learn how to conduct interviews with users and management to
enlist their help in defining the specifications for the fields.
Why Field Specifications Are Important
Despite what you may have heard, the time it takes to establish field
specifications for each field in the database is an investment toward
building consistent data and quality information—you are not wasting
time whatsoever by performing this process. In fact, you’ll waste more
time in the end if you only partially perform this process or neglect it
entirely. Shirking this duty means you’re bound to encounter (and suf-
fer from) inconsistent and erroneous data and inaccurate information.
There are several reasons why field specifications are crucial:
• Field specifications help establish and enforce field-level integrity.
Implementing these specifications enables you to guarantee that
the data in each field is consistent and valid.
• Defining field specifications for each field enhances overall data in-
tegrity. Remember that field-level integrity is one of the four com-
ponents of overall data integrity. Field-level integrity enhances (to
some extent) the table-level integrity you established in the previ-
ous stage of the design process. (This will become apparent when
you work with the logical elements of the field specification.)
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Field-Level Integrity 283
• Defining field specifications compels you to acquire a complete un-
derstanding of the nature and purpose of the data in the database.
Understanding the data means that you can judge whether the
data is truly necessary and important to the organization, and
you can learn how to use it to your best advantage.
• Field specifications constitute the “data dictionary” of the data-
base. Each field specification stores data on the characteristics of
a particular field within the database. The complete set of specifi-
cations you establish for all of the fields in the database composes
a literal dictionary of the database’s structure. This data dictio-
nary is particularly useful when you implement your database in
an RDBMS—you can use it as a guide for creating the fields and
setting their fundamental properties. These specifications will
also help you determine what type of data-entry and data-valida-
tion procedures you need to implement within any user-interface
application you create for the database.
Keep in mind that the levels of consistency, quality, and accuracy of the
data in the database (and information retrieved from that data) are in
direct proportion to the degree that you complete these specifications. It
is paramount that you establish each field specification completely if
your organization depends heavily on the information you retrieve from
the database.
Field-Level Integrity
A field attains field-level integrity after you’ve defined a complete set
of field specifications for the field. Field-level integrity warrants the
following:
• The identity and purpose of a field is clear, and all of the tables in
which it appears are properly identified.
• Field definitions are consistent throughout the database.
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• The values of a field are consistent and valid.
• The types of modifications, comparisons, and operations that can
be applied to the values in the field are clearly identified.
You can guarantee that a field structure is sound and optimally de-
signed when it has a complete set of field specifications and fully con-
forms to the Elements of the Ideal Field. In fact, ensuring that the field
complies with the Elements of the Ideal Field makes defining a set of
specifications a relatively easy task.
If you’ve had any lingering doubt about a particular field’s conformance
to the Elements of the Ideal Field, now is a good time to review that field
once more. If you determine that it is not in conformance, use the ap-
propriate techniques to resolve the problem and make the proper ad-
justments to the table; otherwise, you can begin the process of defining
field specifications for each field in the database. Here are the Elements
of the Ideal Field once again for your convenience.
Elements of the Ideal Field
• It represents a distinct characteristic of the subject of the table.
• It contains only a single value.
• It cannot be deconstructed into smaller components.
• It does not contain a calculated or concatenated value.
• It is unique within the entire database structure.
• It retains a majority of its characteristics when it appears in more
than one table.
Anatomy of a Field Specification
A field specification incorporates various elements that define every at-
tribute of a field. All of the elements within the specification are catego-
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rized as general elements, physical elements, or logical elements. These
element categories enable you to focus on a distinct aspect of the field
as you’re defining the specification, and they provide a way for you to
find a particular element quite easily.
Here are the elements within each category:
• General Elements: Field Name, Parent Table, Label, Specification
Type, Source Specification, Shared By, Alias(es), Description
• Physical Elements: Data Type, Length, Decimal Places, Character
Support, Input Mask, Display Format
• Logical Elements: Key Type, Key Structure, Uniqueness, Null
Support, Values Entered By, Required Value, Default Value,
Range of Values, Edit Rule, Comparisons Allowed, Operations
Allowed
Figure 9.1 shows an example of a Field Specifications sheet. We’ll use
this sheet (or various portions of it) as we work on field specification ex-
amples throughout the remainder of the book.
General Elements
Items under the General Elements category represent the most funda-
mental attributes of the field. They provide information on the field’s
purpose, the name of the table(s) in which the field appears, and the
pseudonyms the field assumes under certain circumstances.
Field Name
This is the set of absolute minimal words that uniquely identifies a par-
ticular field throughout the database. You created and refined field
names earlier in the database-design process (see Chapter 7), so you’ll
just take each name and use it as the setting for this element.
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Figure 9.1. Field Specifications sheet.
Field Name:
Label:
Parent Table:
Shared By:
Alias(es):
Description:
Specification Type:
Source Specification:
ReplicaUnique Generic
Length:
Decimal Places:
Input Mask:
Display Format:
Data Type: Character Support:
Letters (A–Z)
Numbers (0–9)
.Keyboard ( , / $ # %)
Special ( © ® ™ ∑ π)
Key Structure:
Non
Not Determined At This Time
Edit Rule:
Null Support: Nulls Allowed
Enter Now, Edits Allowed
Enter Now, Edits Not Allowed
Enter Later, Edits Allowed
Primary
AlternateForeign
No Nulls
Uniqueness: Non-unique Unique
Required Value: No Yes
Comparisons Allowed:
Range of Values:
Default Value:
Values Entered By: User
Operations Allowed:
System
Key Type:
CompositeSimple
Enter Later, Edits Not Allowed
<> ≠ <=>= Other Fields
Same Field =
Value Expression
<> ≠ <=>== <> ≠ <=>==
All
All
All
÷Same Field Other Fields Concatenation÷
All
All
+
+
x
x
Value Expression All Concatenation÷+ x
Concatenation
General Elements
Physical Elements
Logical Elements
FIELD SPECIFICATIONS
–
–
–
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Parent Table
The table that incorporates a given field within its structure is known as
the field’s parent table. This is the only table in which the field will ap-
pear unless the field is participating in establishing a relationship.
(You’ll learn more about this exception in Chapter 10.) For example,
STUDENTS is the parent table of the STUDFIRST NAME field.
Label
This is an alternate name (typically a shorter form of the field name) by
which you can identify the field within an end-user application interface
that you create for the database. For example, you might use QTY ON
HAND as a label for a field named QUANTITY ON HAND because many people
in the organization are already accustomed to this particular name. La-
bels can be particularly useful when you want to conserve space on a
data-entry screen or squeeze more fields into a particular report.
Avoid the temptation of using the label as the official field name within
the table structure; otherwise, you make it possible for someone to mis-
interpret or incorrectly identify the field. Always use the most precise
and accurate name as the official field name and then use the label (ju-
diciously, of course) within your end-user interface applications. This
will enable you to make a distinction between the two at all times.
Specification Type
The elements you set for a given field depend upon the type of specifica-
tion you define for the field. You can define a specification in three ways:
1. Unique. This is the default specification for all fields except those
that serve as a template for other fields or those that participate
within a table relationship as foreign keys. You can incorporate all
but the Source Specification element for this type of specification,
and the element settings you establish will apply only to the field
indicated in the Field Name element.
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2. Generic. This specification serves as a template for other field spec-
ifications and helps you ensure consistent definitions for fields
that have the same general meaning. For example, you could cre-
ate this type of specification for a generic STATE field and then use it
as the basis for every other STATE field in the database. Fields such
as CUSTSTATE, EMPSTATE, and VENDSTATE all have the same meaning
(they represent a state within the United States), but there is
enough of an obvious distinction between them to require that
they remain separate fields. (If you recall, you learned about ge-
neric fields in Chapter 6 when you were developing the preliminary
field list and in Chapter 7 when you were working with the Ele-
ments of the Ideal Field.)
A generic specification requires you to use a nonspecific field name
and element settings that are as broad and general as possible.
You can, however, incorporate any element except Parent Table,
Label, Shared By, Alias(es), and Source Specification.
3. Replica. This is the default specification for a field based on a ge-
neric field or a field that serves as a foreign key within a table rela-
tionship, and it draws a majority of its element settings from an
existing specification. You can incorporate elements that were not
already incorporated by the source specification, and you can alter
any element settings drawn from the source specification.
You’ll learn how to define each type of specification in the section “Using
Unique, Generic, and Replica Field Specifications” later in the chapter.
Source Specification
This element is set only on a Replica specification and indicates the
name of the specific field specification upon which the current specifica-
tion is based. (You’ll see a good example of this element in the next sec-
tion as well.)
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Shared By
This element indicates the names of other tables that share this field.
The only table names that should appear here are those that have an
explicit relationship to the field’s parent table. For example, assume you
have a data table called EMPLOYEES that is related to two subset ta-
bles called PART-TIME EMPLOYEES and FULL-TIME EMPLOYEES via a
field called EMPLOYEE ID NUMBER. As you create a field specification for
EMPLOYEE ID NUMBER, you would use “PART-TIME EMPLOYEES, FULL-
TIME EMPLOYEES” as the setting for this element.
Alias(es)
This is a name (or set of names) that you use for the field in very rare cir-
cumstances. One instance in which you would use an alias is when there
must be two occurrences of the field in the same table. Let’s assume that
an organization is accustomed to identifying its employees by unique val-
ues within an EMPLOYEE ID NUMBER field. Now, consider the SUBSIDIARIES
table structure in Figure 9.2 (this is a partial structure only).
Figure 9.2. A table requiring two occurrences of the same field.
Table Structures
Subsidiaries
Employee ID Number
Subsidiary ID Number
Subsidiary Name
Employee ID Number
SubsStreet Address
SubsCity
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In this instance, each subsidiary has a president and a vice president.
Both of these individuals must be represented in the table because of
their positions within the subsidiary organization, so there are two EM-
PLOYEE ID NUMBER fields in the table structure. Proper database design,
however, dictates that there can only be one occurrence of this field
within the table; there is an obvious problem here. The only solution is
to use an alias for one or both occurrences of the EMPLOYEE ID NUMBER
field. For instance, you could (for sake of clarity) use PRESIDENT ID as an
alias for the first occurrence of EMPLOYEE ID NUMBER and VICE PRESIDENT ID
as an alias for the second occurrence of EMPLOYEE ID NUMBER. With the
aliases in place, both employees are properly represented within the ta-
ble. Figure 9.3 shows the revised table structure.
Although using an alias is acceptable under these circumstances, you
should use them very judiciously; otherwise, they can become difficult
to manage and maintain, eventually conceal or disguise the true mean-
ing of the original fields, and cause you to misunderstand what the data
Figure 9.3. Using aliases in place of the EMPLOYEE ID NUMBER fields.
Table Structures
Subsidiaries
President ID Number
Subsidiary ID Number
Subsidiary Name
Vice President ID Number
SubsStreet Address
SubsCity
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actually represents. This issue will become even clearer when you begin
to establish table relationships.
Description
This is a complete interpretation of the field. Composing a field descrip-
tion is extremely beneficial because it forces you (and everyone in the
organization) to think carefully about the nature of the data that will be
stored in the field. You can be relatively sure that the field requires fur-
ther refinement if you have difficultly composing a suitable description.
Earlier in the database-design process, you learned a set of guidelines
for composing a table description. Similarly, there is a set of guidelines
that governs how you compose a proper field description.
Guidelines for Composing a Field Description
• Use a statement that accurately identifies the field and clearly
states its purpose. The description should supplement the field
name in terms of defining what the field represents. It should also
state the field’s role within the table or its relationship to the ta-
ble’s subject. Here’s an example of such a description:
CustCity—the metropolitan area in which a customer re-
sides or conducts business. This is an integral component
of a customer’s complete address.
• Write a clear and succinct statement. The description should be
free of confusing sentences or ambiguous phrases. Although the
description should be as complete as possible, use the minimum
number of words necessary to convey the required information.
As you’ve seen with table descriptions, verbose statements are dif-
ficult to read and understand.
• Refrain from restating or rephrasing the field name. Neither of these
practices does anything to illuminate the identity or purpose of the
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field. Remember that the purpose of a description is to provide a
complete interpretation of the field. Here’s an example of a poor
description:
CustLast Name—the last name of a customer.
A description is far more useful when you write it in this manner:
CustLast Name—the surname of a customer, whether
original or by marriage, that we use in all formal commu-
nications and correspondence with that customer.
• Avoid using technical jargon, acronyms, or abbreviations. Although
some people within the organization will understand these types
of idioms, its better for you to use terminology that everyone un-
derstands. Remember that a description must be as clear as pos-
sible to anyone who reads it. For example, you should avoid this
type of statement:
Employee ID Number—a unique number used to identify
an employee within the organization. It is a component of
the SSP.
The problem with this description is that there is no inherent way
to determine the meaning of the acronym SSP. You could resolve
this problem by spelling out the complete term, but it would be
better for you to restate the purpose of the field.
• Do not include implementation-specific information. There’s no rea-
son to include the fact that a given field appears on a particular
data-entry screen or is used within a specific piece of program-
ming code. This type of information is more appropriate for the im-
plementation phase of the overall database-development process.
• Do not make this description dependent upon the description of an-
other field. Each description should be as complete as possible
and independent of every other description in the database. Inter-
dependent descriptions introduce unnecessary confusion and can
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Anatomy of a Field Specification 293
inadvertently obscure the field’s true identity and purpose. Avoid
using a description such as this:
Item Reorder Level—minimum number of items that must
exist for a particular product. (See description for Quantity
On Hand).
• Do not use examples. As you learned in Chapter 7, using exam-
ples in a description is a bad idea because they depend on
supplemental information to convey their full meaning. You can
ensure that a description is clear and succinct by keeping it abso-
lutely free of examples.
Figure 9.4 shows the General Elements section of a Field Specifications
sheet for an EMPLOYEE ID NUMBER field.
Physical Elements
This category pertains to the structure of a field. Its elements are ex-
pressed in general terms because each RDBMS program implements
them in a slightly different manner. Establishing these elements dur-
ing this phase of the design process helps you ensure consistent field
Figure 9.4. The General Elements category for an EMPLOYEE ID NUMBER field.
A unique number used to identify each employee within our organization. It is assigned during the first day of employee orientation and remains with the employee throughout the duration of his or her employment.
Full-Time Employees, Part-Time Employees, Customers
Employee #
Employees
Employee ID Number
General Elements
Field Name:
Label:
Parent Table:
Shared By:
Alias(es):
Description:
Source
Specification Type:
Specification:
x GenericUnique Replica
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definitions throughout the database and reduces the time it will take
you to implement the field structures in an RDBMS program.
Data Type
This element indicates the nature of the data that the field stores.
In Chapter 1, you learned that Structured Query Language, or SQL, is
the standard language used to create, modify, maintain, and query rela-
tional databases. SQL is actually a fully documented standard set forth
jointly by the American National Standards Institute (ANSI) and the In-
ternational Organization for Standardization (ISO). Although the cur-
rent version of the standard (as of this writing) is SQL/3, most major
RDBMS programs implement much of the previous version, SQL/92.
The SQL standard defines seven major data types, and each data type
has one or more uniquely named variations. Here’s a brief definition of
each data type.
Character This data type stores a fixed- or varying-
length character string of one or more print-
able characters. A fixed-length Character
data type is known as CHARACTER or CHAR,
and a varying-length Character data type is
known as CHARACTER VARYING, CHAR
VARYING, or VARCHAR.
National Character This data type is the same as the Character
data type, but it can also store characters
from foreign-language character sets. A fixed-
length National Character data type is known
as NATIONAL CHARACTER, NATIONAL
CHAR, and NCHAR, and a varying-length Na-
tional Character data type is known as NA-
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Anatomy of a Field Specification 295
TIONAL CHARACTER VARYING, NATIONAL
CHAR VARYING, and NCHAR VARYING.
Bit This data type stores strings of binary num-
ber sequences, such as digitized images and
sound waves. This data type is often referred
to as BIT or BIT VARYING.
Exact Numeric This data type stores whole numbers and
numbers with decimal places. Most RDBMS
programs implement an Exact Numeric as NU-
MERIC, DECIMAL (DEC), INTEGER (INT), and
SMALLINT, and each variation determines the
range of values that the field will accept.
Approximate Numeric This data type stores numbers with decimal
places and exponential numbers. Most
RDBMS programs implement an Approximate
Numeric as FLOAT, REAL, and DOUBLE PRE-
CISION, and each variation determines the
range of values that the field will accept.
DateTime This data type is commonly known as TIME-
STAMP in most RDBMS programs, and it
stores dates, times, and combinations of both.
Note that the implementation of this data type
varies widely among RDBMS programs, so you
must make absolutely certain that you refer to
the RDBMS’s documentation to determine how
the RDBMS handles dates and times.
Interval This data type stores the quantity of time be-
tween two DateTime values, expressed either
as year, month, year/month day, time, or
day/time. Most major database systems do
not yet support this data type, so you needn’t
worry about it for now.
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Many RDBMS programs provide additional data types beyond those
specified by the standard, which are known as extended data types. Ex-
amples of extended data types include MONEY/CURRENCY, BOOLEAN
(for True or False values), SERIAL/ROWID (for unique row identifiers),
and BYTE/BLOB (for unstructured binary data).
I’ve presented the SQL standard data types because you will encounter
them (or variations thereof) in practically every RDBMS program. I have
not provided much detail on these data types, however, because they
are not implemented consistently across all RDBMS programs; you
must consult your RDBMS’s documentation to determine which data
types the RDBMS supports and how the RDBMS implements them.
You can use any of the SQL data types (except Interval) as the setting
for the Data Type element of a given specification. Due to their inconsis-
tent implementation, however, I recommend that you use one of the fol-
lowing general data types as the setting for this element instead.
Alphanumeric This data type stores any combination of letters,
numbers, keyboard characters, or special charac-
ters. Keyboard characters include the comma, dollar
sign, exclamation mark, percentage sign, and period.
Special characters include the copyright symbol, the
trademark symbol, and the symbol for pi.
Numeric This data type stores only whole numbers and real
numbers. It will not accept numbers with leading ze-
roes (e.g., 0000234) because they are not genuine
numbers.
DateTime This data type stores dates, times, or a combination
of both.
These data types are quite suitable for indicating the nature of the data
that the field stores, and they are certainly much easier for users and
management to understand. Using general data types will help you
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Anatomy of a Field Specification 297
avoid unnecessary confusion, especially when you’re reviewing the
specification with users and management.
Length
This element specifies the total number of characters that a user can
enter for any given field value. The RDBMS program you use to imple-
ment the database will determine the maximum number of characters
you can set for this element. Although you can theoretically set the
Length element for any data type, you should be aware that some
RDBMS programs do not allow you to specify a length for a numeric
field. Instead, the RDBMS program sets the length of a numeric field
based on the type of number the field stores, such as an integer, a long
integer, or a real number.
Decimal Places
This denotes the number of digits to the right of the decimal point in a
real number. The number of digits determines the real number’s preci-
sion. For example, many businesses require that all currency values
have four digits of precision to the right of the decimal point.
Character Support
This element indicates the type of characters that a user can enter into
a given field value. Setting and enforcing this element helps you ensure
that the user cannot introduce meaningless data into the field, thus en-
hancing field-level integrity.
❖ Note I use these general data types as the basis for all further data type references and examples throughout the remainder of
the book.
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Let’s say you’re working with a CUSTSTATE field and its data type is al-
phanumeric. This data type is appropriate for the field because it allows
a user to incorporate letters as part of a given field value. But it also al-
lows him to use numbers, keyboard characters, and extended charac-
ters, which means that he can enter a meaningless value into the field—
there are no state names or state abbreviations that contain characters
other than letters. You solve this problem by using the Character Sup-
port element to define the characters that the user can incorporate
within a field value. (I address the issue of a valid combination of letters
in the “Logical Elements” section.)
You can choose to include or exclude any of the following types of
characters:
• Letters—all letters of the alphabet including foreign language let-
ters such as é and ñ.
• Numbers—0 through 9.
• Keyboard characters—any standard character other than
letters and numbers, such as asterisk, ampersand, bracket,
caret, comma, equals sign, exclamation point, parenthesis,
percent sign, period, pound sign, question mark, quote, semi-
colon, slash, or vertical bar. Note that the Field Specifications
sheet includes examples of the characters that belong to this
category.
• Special characters—any character that you can produce only
through specific combinations of standard keys and the CTRL,
ALT, and SHIFT keys, or with the aid of a special software pro-
gram. Characters in this category include complex mathematical
symbols, the copyright symbol, fractions, the symbol for pi, and
the trademark symbol. The Field Specifications sheet includes
examples of these characters as well.
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Input Mask
This element specifies the manner in which a user should enter data
into the field. For example, there are many ways to enter a date, such as
“01/01/02,” “01-01-02,” and “01-Jan-2002.” Using an input mask helps
you ensure that a user enters values into the field consistently and (in
this case) prevents confusion over the meaning of the date sequence.
RDBMS programs implement input masks in various ways, so you
should use a relatively generic setting for this element. (You can assign
multiple input masks, if appropriate.) For example, you could use
“mm/dd/yy” as the input mask for a date field. This mask indicates the
sequence of the date components (month, day, year), the structure of
the date (two numbers per component, e.g., 05/16/02), and the date
component separator (the slash).
Display Format
This element governs the appearance of a field’s value when it is displayed
on a screen or printed within a document. A display format enables you to
present the field value in a more meaningful or readable fashion than the
manner in which it was entered. For example, “03/13/88” might be the
way you enter a given date, but “March 13, 1988” is much easier to read
and comprehend.
Use a generic setting for this element, just as you did with the Input
Mask; RDBMS programs implement display formats in various ways as
well. For example, you can use “Month Day, Year” as a display format
for a DATE HIRED field. You can also use a complete sentence to indicate a
display format, such as the one in this example of a display format set-
ting for a COMPANY NAME field.
Each word should start with a capital letter.
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Figure 9.5 shows the Physical Elements section of a Field Specifications
sheet for an EMPLOYEE ID NUMBER field.
Logical Elements
This category pertains mainly to the values within a field. Its elements
govern matters such as whether each value should be unique, when a
value should be entered, whether a value can be edited, and the types of
comparisons and operations that can be performed on each value. Set-
ting these elements helps you establish and enforce a large part of field-
level integrity.
Key Type
This element designates a field’s role within a table, which you identified
as you were establishing a primary key for the table. As you already
know, a field can serve as a non-key, a primary key, or an alternate key.
In Chapter 10, you’ll learn all about foreign keys and when to designate
a field as a foreign key on the Field Specifications sheet.
Key Structure
This element denotes whether a field designated as a primary key is act-
ing as a simple (single-field) primary key or as part of a composite (mul-
tifield) primary key.
Figure 9.5. The Physical Elements category for an EMPLOYEE ID NUMBER field.
Physical Elements
Length:
Decimal Places:
Input Mask:
Display Format:
Data Type: Character Support:
Special ( © ® ™ ∑ π)
Keyboard ( . , / $ # %)Letters (A–Z)
Numbers (0–9)x
Numeric
4
0
####
0000
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Uniqueness
This element indicates whether a field’s values are unique. You set it as
“Unique” when the Key Type element is set to “Primary”; otherwise,
you’ll typically set this element as “Non-unique.”
When you work with a non-key field, think about how its values are go-
ing to be used so that you can determine whether they should be
unique. Consider the DEPARTMENTS table structure in Figure 9.6.
In this example, the EMPLOYEE ID NUMBER field identifies the person who
manages a particular department. Assuming that a person is allowed to
manage only one department at any given time, the values in this field
should be unique; therefore, you should set the Uniqueness element for
this field as “Unique.”
Null Support
This specifies whether a field accepts null values. “No Nulls” is the set-
ting you’ll commonly use for this element, especially when a field serves
as a primary key or an alternate key, or when the field’s Required Value
element is set to “Yes.” You can set this element to “Nulls Allowed,” how-
ever, when there is a valid reason for a field to accept null values. A
CUSTCOUNTY field, for example, must accept nulls because a customer
Figure 9.6. Should the values of EMPLOYEE ID NUMBER be unique?
Table Structures
Departments
Employee ID Number
Department ID Number
Department Name
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may not know the name of the county in which she lives. (Of course, it
will no longer be null once she supplies the county name.)
Remember that a null does not represent a blank—it represents a miss-
ing or unknown value. Users commonly make the mistake of using a
blank to represent a meaningful value, such as “None,” “Not Applicable,”
“No Response,” and “Not Wanted.” If these values are valid for a particu-
lar field, then make sure you include them in the Range of Values ele-
ment for the field. Above all, use nulls judiciously and do not use blanks!
Values Entered By
This element indicates the source of a field’s values. Either a user will
enter values into the field manually or a database application program
will enter them automatically; the application program can provide val-
ues for the field only if the person who developed the program provided
a means for it to generate the values. Note that the setting that repre-
sents the database application program is “System.”
Required Value
This denotes whether a user is required to enter a value for a field. Al-
though you’ll typically set this element to “No” for most of the fields in a
table, you must set it to “Yes” when the field serves as the primary key.
You may also need to set Required Value to “Yes” for a field such as
CUSTZIPCODE—a letter or package you send to a given customer must in-
clude a zip code in order for the Postal Service to handle it properly and
accurately.
Default Value
This is a value that a user can enter into a field when a more appropri-
ate value is not yet available and nulls are disallowed. Use a default
value very judiciously, and only if it is meaningful. For example, “WA” is
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Anatomy of a Field Specification 303
a meaningful default value for a CUSTSTATE field when the vast majority
of your customers live in Washington state. Conversely, “01/01/96” is
not a good default value for a DATE HIRED field because it is a completely
arbitrary value that has no real meaning.
Range of Values
This element specifies every possible valid value for a field. You can set
this element in various ways, such as with a lower and upper limit (1,000
to 9,999) or with a specific list of values (“WA,” “OR,” “ID,” “MT”). There
are three categories under which you can establish a range of values:
1. General—a complete collection of every possible value for this field.
For example, the general range of values for a CUSTSTATE field might
include all valid abbreviations for every state in the United States.
2. Integrity specific—a collection of values based on the field’s role
within a table relationship. (You’ll learn all about this category in
Chapter 10.)
3. Business specific—a collection of values generated by a particular
business requirement. Organizations commonly have various re-
quirements that limit the range of values for a field. In an organiza-
tion that conducts its business strictly in the Pacific Northwest, for
example, the valid range of values for a CUSTSTATE field are “WA,”
“OR,” “ID,” and “MT.” (You’ll learn more about this category in
Chapter 11.)
You’re concerned only with the general range of values during this stage
of the database-design process, and you’ll revisit the Range of Values el-
ement later when you establish table relationships and business rules.
It’s important to note that “Other” and “Miscellaneous” are two values
that you do not want to set within any category of the Range of Values
element. Both values are nonspecific and absolutely meaningless within
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this context and are a sign of mental laziness in that their very presence
indicates a need to review the field for possible refinement. You can
avoid unnecessary confusion and potential problems by refraining from
using these values.
Edit Rule
This element designates at what point a user can enter a value into a
field and whether he can modify that value. You set this element to one
of these four options:
1. Enter Now, Edits Allowed. A user must enter a value for this field
when she creates a new record in the field’s parent table. She can
then edit the value at any time.
2. Enter Later, Edits Allowed. A user has the option of entering a value
for this field when he creates a new record in the field’s parent
table. This does not imply in any way that the field’s value can be
null for all time; the user must enter a value for this field at some
point in the near future. After he’s entered the value, he can then
edit it at any time.
3. Enter Now, Edits Not Allowed. A user must enter a value for this
field when she creates a new record in the field’s parent table, but
she cannot edit it at any time whatsoever.
4. Enter Later, Edits Not Allowed. A user has the option of entering a
value for this field when he creates a new record in the field’s par-
ent table. This does not imply in any way that the field’s value can
be null for all time; the user must enter a value for this field at
some point in the near future. After he’s entered the value, he can-
not edit it at any time whatsoever.
You should use a default value when you set the Edit Rule element to
the second or fourth option; this will keep the field’s value from being
null until such time that the user enters an appropriate value.
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Comparisons Allowed
This indicates the types of comparisons a user can apply to a given field
value when he’s retrieving information from the field. There are six
types of comparisons: equal to (=), not equal to (≠), greater than (>), less than (<), greater than or equal to (>=), and less than or equal to (<=).
This element also indicates whether a user can compare a given field
value to any of the following:
• Another value within the same field. When a field serves as a pri-
mary key, this option applies to the values of related foreign key
fields. (You’ll learn more about this in the next chapter.)
• A value of another field within the parent table or from some other
table in the database.
• A value expression, which is some form of operation involving
field values, literal values, or a combination of both. It returns a
single value that you can then use for the comparison: (RETAIL
PRICE – 2.50) is an example of a value expression.
Controlling the types of comparisons a user can apply to the field’s val-
ues enables you to keep him from making meaningless comparisons.
Let’s say that he’s working with an EMPLOYEE ID NUMBER field based on a
numeric data type. Unless you indicate otherwise, he can make a com-
parison such as this one:
Is an Employee ID Number in the Employees table greater than
or equal to an Employee ID Number in the Part-Time Employees
table?
Although a “greater than or equal to” comparison is generally acceptable
in a numeric field, it is not appropriate in this instance; there is no valid
reason for him to make this type of comparison.
Similarly, it would be pointless for him to make a comparison between a
given EMPLOYEE ID NUMBER value and the value of another numeric field
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306 Chapter 9 Field Specifications
within the EMPLOYEES table or some other table within the database;
therefore, a comparison such as this is invalid:
Is an Employee ID Number in the Employees table greater than
or equal to a Quantity On Hand in the Products table?
It is both suitable and reasonable, however, for him to make a compari-
son between a given EMPLOYEE ID NUMBER value within the EMPLOYEES
table and another EMPLOYEE ID NUMBER value within a related data table
or related subset table. This comparison, then, is a valid one:
Is an Employee ID Number in the Employees table equal to an
Employee ID Number in the Part-Time Employees table?”
There are instances when it is perfectly suitable for the user to compare
a particular value of one field to the value of a completely different field.
For example, it is totally logical for him to make the following compari-
son between a DATE SHIPPED field and a DATE ORDERED field:
Is the current value of Date Shipped greater than or equal to the
current value of Date Ordered?
It’s fortunate that he can make this type of comparison—he certainly
doesn’t want the value of DATE SHIPPED to be earlier than the value of
DATE ORDERED!
As you set the Comparisons Allowed element for a given field, think
about how you’re going to use the field’s values so that you can desig-
nate the appropriate comparisons. It’s very likely that you’ll review this
element later in the design process when you establish table relation-
ships and define business rules.
Operations Allowed
This element specifies the types of operations that a user can perform
on the field’s values. There are five types of operations: addition (+),
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Anatomy of a Field Specification 307
subtraction (–), multiplication (×), division (÷), and concatenation. (Obvi- ously, any combination of these operations is valid as well.) This ele-
ment also indicates whether an operation can incorporate any of the
following:
• Another value within the same field
• A value from another field within the parent table or from some
other table in the database
• The result of a value expression (which, as you recall, is itself
some form of operation involving field values, literal values, or a
combination of both, that returns a single value)
You can prevent the user from defining meaningless operations by limit-
ing the types of operations that he can perform on the field’s values.
Let’s consider the EMPLOYEE ID NUMBER, DATE SHIPPED, and DATE ORDERED
fields once again. There is no reason for the user to perform mathemat-
ical operations on a pair of EMPLOYEE ID NUMBER values within the EM-
PLOYEES table, nor is there any reason for him to perform such
operations using a given EMPLOYEE ID NUMBER value and some other nu-
meric field’s value. In the case of the DATE SHIPPED field, however, it is
suitable to perform some of these operations using a given DATE SHIPPED
value and the value of some other appropriate date field within the data-
base. For example, the user might need to subtract DATE ORDERED from
DATE SHIPPED to determine the time that elapsed between the date that
the customer placed the order and the date that the items within the or-
der were shipped to the customer.
As you set the Operations Allowed element for a given field, think about
how you’re going to use the field’s values so that you can designate the
appropriate operations. It’s very likely that you’ll review this element
later in the design process as you define business rules.
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Figure 9.7 shows the Logical Elements section of a Field Specifications
sheet for an EMPLOYEE ID NUMBER field.
Using Unique, Generic, and Replica Field Specifications
Earlier in this chapter, you learned that you could define a specification
as Unique, Generic, or Replica. You can ensure that you define the ap-
propriate type of specification for a given field by following these simple
guidelines:
Figure 9.7. The Logical Elements category for an EMPLOYEE ID NUMBER field.
Logical Elements
Key Structure:
Non
Not Determined At This Time
Edit Rule:
Null Support: Nulls Allowed
Enter Now, Edits Allowed
Enter Now, Edits Not Allowed
Enter Later, Edits Allowed
Primary
AlternateForeign
No Nulls
Uniqueness: Non-unique Unique
Required Value: No Yes
Comparisons Allowed:
x
x
x
x
x
Range of Values:
Default Value:
Values Entered By: User
Operations Allowed:
Systemx
Key Type:
CompositeSimplex
Enter Later, Edits Not Allowed
<> <=>=
Other Fields
Same Fieldx =x
Value Expressionx <> <=>==
<> <=>==x
All
All
All
Same Field
Other Fields Concatenation
All
All
+
+
x
x
Value Expression All Concatenation+ x
Concatenation
1000–9999
≠ ≠ ≠
÷ ÷ ÷
–
–
–
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Using Unique, Generic, and Replica Field Specifications 309
• Use a Unique specification for any field that will appear only once
within the entire database or for a field that serves as a primary key.
• Use a Generic specification for a field that serves as a template for
other fields within the database. Remember to use a nonspecific
field name and element settings that are as broad and general as
possible.
• Use a Replica specification for a field that you base on a given
generic field or for a field that serves as a foreign key within a
table relationship.
Figure 9.8 shows the complete Unique field specification for a VENDOR ID
NUMBER field.
Here are a few things to note about this specification:
1. This field also appears in the PRODUCTS table, as indicated by the
Shared By general element. This is both reasonable and necessary
because each product must be associated with a specific vendor.
(You’ll learn more about this type of issue in the next chapter.)
2. Examine the settings for the Uniqueness, Null Support, Required
Value, and Edit Rule logical elements. They are set in this manner
because the Key Type element is set to “Primary.” You should, in
fact, use these element settings for any field that serves as a pri-
mary key.
3. The Comparisons Allowed logical element is set to “Same Field—
Equals” so that a user can compare VENDOR ID NUMBER values in the
VENDORS table to VENDOR ID NUMBER values in the PRODUCTS table.
4. The Comparisons Allowed logical element is also set to “Value Ex-
pression—Equals” so that a user can compare VENDOR ID NUMBER
values to some arbitrary numeric value.
Figure 9.9 shows the complete Generic field specification for a generic
STATE field.
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Figure 9.8. Unique field specification for the VENDOR ID NUMBER field.
General Elements
Field Name:
Label:
Parent Table:
Shared By:
Alias(es):
Description:
Specification Type:
Source Specification:
ReplicaUnique Generic
Physical Elements
Length:
Decimal Places:
Input Mask:
Display Format:
Data Type: Character Support:
Letters (A–Z)
Numbers (0–9) Special ( © ® ™ ∑ π)
Logical Elements
Key Structure:
Non
Not Determined At This Time
Edit Rule:
Null Support: Nulls Allowed
Enter Now, Edits Allowed
Enter Now, Edits Not Allowed
Enter Later, Edits Allowed
Primary
AlternateForeign
No Nulls
Uniqueness: Non-unique Unique
Required Value: No Yes
Comparisons Allowed:
Range of Values:
Default Value:
Values Entered By: User
Operations Allowed:
System
Key Type:
CompositeSimple
Enter Later, Edits Not Allowed
<> ≠ <=>= Other Fields
Same Field =
Value Expression
<> ≠ <=>== <> ≠ <=>==
All
All
All
÷Same Field Other Fields Concatenation÷
All
All
+
+
x
x
Value Expression All Concatenation÷+ x
Concatenation
100000–200000
x
x
x
x
x x x x
x
x
A unique number used to identify each vendor that supplies our organization with goods or services. It is assigned when we place the first order for such goods or services with the vendor.
x
Numeric
6
0
######
000000
Products
Vendor #
Vendors
Vendor ID Number
.Keyboard ( , / $ # %)
–
–
–
FIELD SPECIFICATIONS
x
x
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Using Unique, Generic, and Replica Field Specifications 311
Figure 9.9. Generic field specification for a generic STATE field.
General Elements
Field Name:
Label:
Parent Table:
Shared By:
Alias(es):
Description:
Specification Type:
Source Specification:
ReplicaUnique Generic
Physical Elements
Length:
Decimal Places:
Input Mask:
Display Format:
Data Type: Character Support:
Letters (A–Z)
Numbers (0–9) Special ( © ® ™ ∑ π)
Logical Elements
Key Structure:
Non
Not Determined At This Time
Edit Rule:
Null Support: Nulls Allowed
Enter Now, Edits Allowed
Enter Now, Edits Not Allowed
Enter Later, Edits Allowed
Primary
AlternateForeign
No Nulls
Uniqueness: Non-unique Unique
Required Value: No Yes
Comparisons Allowed:
Range of Values:
Default Value:
Values Entered By: User
Operations Allowed:
System
Key Type:
CompositeSimple
Enter Later, Edits Not Allowed
<> <=>=
Other Fields
Same Field =
Value Expression
<> <=>==
<> <=>==
All
All
All
Same Field
Other Fields Concatenation
All
All
+
+
x
x
Value Expression All Concatenation+ x
Concatenation
x
x
x
x
x x
x
x
x x
State
A state or territory within the United States in which a person, organization, or institution resides or conducts business.
Alphanumeric
2
None
AA
Both letters should be capitalized.
All state abbreviations recognized by the United States Postal Service.
x x
x x
≠ ≠ ≠
÷ ÷ ÷
.Keyboard ( , / $ # %)
FIELD SPECIFICATIONS
–
–
–
State
State
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Take note of these particular items:
1. The description is very general, as it should be for this type of
specification.
2. The setting of the Display Format physical element is in the form
of an instruction. This demonstrates that you have a great deal of
flexibility in the way you set this element.
3. The Range of Values logical element is appropriately broad.
4. The Comparisons Allowed logical element is set to “Value Expres-
sion—Equals” so that a user can compare STATE values to some
arbitrary two-character alphanumeric value.
5. The Operations Allowed logical element is set to “Other Fields—
Concatenation” so that a user can concatenate a given STATE value
to the value of some other alphanumeric field.
6. The Operations Allowed logical element is also set to “Value Ex-
pression—Concatenation” so that a user can concatenate a given
STATE value to some arbitrary alphanumeric value.
This field (and its specification) now serves as a template for all other state
fields you create in the database. For example, you can create a VENDSTATE
field based on the generic STATE field. You’ll define a Replica specification
for the VENDSTATE field that is based on the STATE field’s Generic specifica-
tion. Although the VENDSTATE field’s Replica specification draws its initial
element settings from the STATE field’s Generic specification, you can mod-
ify any of the Replica specification’s element settings so that you can com-
pletely customize them for the VENDSTATE field. Figure 9.10 shows the
customized Replica field specifications for the VENDSTATE field.
Here are a few things to note about this specification:
1. The field name (VENDSTATE) accurately denotes what the field
represents.
2. The label (“State”) is what the user will see on visual displays and
printed documents.
From the Library of Stephen Benoit
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Using Unique, Generic, and Replica Field Specifications 313
Figure 9.10. Customized Replica field specification for the VENDSTATE field.
General Elements
Field Name:
Label:
Parent Table:
Shared By:
Alias(es):
Description:
Specification Type:
Source Specification:
ReplicaUnique Generic
Physical Elements
Length:
Decimal Places:
Input Mask:
Display Format:
Data Type: Character Support:
Letters (A–Z)
Numbers (0–9) Special ( © ® ™ ∑ π)
Logical Elements
Key Structure:
Non
Not Determined At This Time
Edit Rule:
Null Support: Nulls Allowed
Enter Now, Edits Allowed
Enter Now, Edits Not Allowed
Enter Later, Edits Allowed
Primary
AlternateForeign
No Nulls
Uniqueness: Non-unique Unique
Required Value: No Yes
Comparisons Allowed:
Range of Values:
Default Value:
Values Entered By: User
Operations Allowed:
System
Key Type:
CompositeSimple
Enter Later, Edits Not Allowed
<> <=>=
Other Fields
Same Field =
Value Expression
<> <=>==
<> <=>==
All
All
All
Same Field
Other Fields Concatenation
All
All
+
+
x
x
Value Expression All Concatenation+ x
Concatenation
x
x
x
x
x x
x
x
x x
x x
x x
≠ ≠ ≠
÷ ÷ ÷
VendState
Vendors
The state in which the vendor's headquarters are located. This data is a component of the vendor's overall mailing address.
Alphanumeric
2
Both letters should be capitalized.
None
AA
WA
CA, ID, MT, OR, WA
State
.Keyboard ( , / $ # %)
–
–
–
State
FIELD SPECIFICATIONS
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314 Chapter 9 Field Specifications
3. The Source Specification general element properly references the
generic STATE field’s specification.
4. The Description element is now specific to this field. Recall that the
description is more general in the source specification.
5. A default value has been set for this field; there is no such value in
the source specification.
6. The Range of Values element is now specific to this field; it was
much broader in the source specification.
In the next chapter, you’ll learn how to define a Replica field specifica-
tion for a field that serves as a foreign key.
Defining Field Specifications for Each Field in the Database
Now that you have all the necessary fields assigned to each table and
you understand the various elements within a field specification, you
can begin the process of defining a field specification for each field in
the database. It will take you a considerable amount of time to com-
plete this process, but remember that you’re working diligently to es-
tablish field-level integrity by ensuring that the data is consistent,
valid, and as free from errors as possible. All your hard work will pay
great dividends because the information you retrieve from the database
will always be timely and accurate, and you will have a reliable set of
structural blueprints you can use when you implement the database in
an RDBMS program.
You can ensure that the specifications are as complete and accurate as
possible by working with both users and management to define them.
They can provide insights into the data and can be of special assistance
in refining the specification’s logical elements. You don’t have to speak
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Defining Field Specifications for Each Field in the Database 315
with everyone in the organization, but you do want to assemble and
meet with a representative number of people who are very familiar with
the data and how it is used. Schedule as many meetings as are neces-
sary (or possible) to complete the interview process, and take the time
you need to be as thorough as you can. Above all, do not rush through
this phase! Doing so just diminishes the benefits of your overall efforts
and increases your chances of making unnecessary mistakes.
The best strategy for this task is to define as many of the specifications
as you can (as completely as possible) and then work with the partici-
pants to complete the rest. As you work with a field’s specifications, use
your best judgment to define the settings for each element. Don’t worry
if your settings seem slightly incorrect or if you have difficulty providing
settings for some of the elements—you’re going to review them with the
participants anyway. After you’ve defined specifications for all of the
fields that are familiar to you, begin meeting with the participants to
work on specifications for the remaining fields.
Your first order of business during the initial meeting is to explain the
various elements within a field specification and make sure that every-
one understands them as much as possible. Providing the participants
with a brief and succinct education on the specification’s elements gives
them the knowledge they need to help you define a specification prop-
erly. (In subsequent meetings, just review the elements to make certain
that everyone remembers what they represent.)
Next, review all of the specifications you’ve defined and ask the partici-
pants whether the settings for the elements are suitable and correct. In
some cases, the participants will reveal new information about a field
that will affect that field’s specification. For example, a participant may
remember (prompted by some topic in the discussion) that there is a
specific set of values that has always been used for a particular field;
therefore, you set the field’s Range of Values element to reflect this new
information. Make sure that you examine each part of the specification
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316 Chapter 9 Field Specifications
and then move on to the next specification when the participants have
no further suggestions for refinement. Repeat this process for each
specification.
Now, work with the participants on the specifications you were unable
to define or complete. Try to work with the people who are most familiar
with the fields under discussion because they are likely to know what
settings should be used for the Logical Elements category. Identify the
appropriate element settings for each field and mark them on the Field
Specifications sheet. After you’ve defined specifications for every field in
the database, the entire process is complete.
The design of the new database is now close to completion. In the next
chapter, you’ll learn how to establish relationships between the tables in
the database. Relationships are important because they allow a view to
draw data from multiple tables simultaneously.
Now that you have all the appropriate fields assigned to the tables in the
Mike’s Bikes database, it’s time to define field specifications for each
field. Before you meet with Mike and his staff, you define as many field
specifications as you can. None of the tables are unusual in any way,
and the fields are pretty straightforward, so you have little difficulty in
defining the specifications. Figure 9.11 shows the specification for the
PRODUCT DESCRIPTION field in the PRODUCTS table.
Now you meet with Mike and his staff to discuss the field specifications
you’ve defined. No one seems to have problems with any of the specifica-
tions; everyone confirms that all of the element settings seem suitable
and correct. You do have a question, however, regarding the CATEGORY
field in the PRODUCTS table: You want to know the appropriate setting
for the Range of Values element. The response to your question is
mixed—no one seems to know the complete list of categories that are
CASE STUDY
From the Library of Stephen Benoit
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Case Study 317
Figure 9.11. Field specification for the PRODUCT DESCRIPTION field.
General Elements
Field Name:
Label:
Parent Table:
Shared By:
Alias(es):
Description:
Specification Type:
Source Specification:
ReplicaUnique Generic
Physical Elements
Length:
Decimal Places:
Input Mask:
Display Format:
Data Type: Character Support:
Letters (A–Z)
Numbers (0–9) Special ( © ® ™ ∑ π)
Logical Elements
Key Structure:
Non
Not Determined At This Time
Edit Rule:
Null Support: Nulls Allowed
Enter Now, Edits Allowed
Enter Now, Edits Not Allowed
Enter Later, Edits Allowed
Primary
AlternateForeign
No Nulls
Uniqueness: Non-unique Unique
Required Value: No Yes
Comparisons Allowed:
Range of Values:
Default Value:
Values Entered By: User
Operations Allowed:
System
Key Type:
CompositeSimple
Enter Later, Edits Not Allowed
<> <=>=
Other Fields
Same Field =
Value Expression
<> <=>==
<> <=>==
All
All
All
Same Field
Other Fields Concatenation
All
All
+
+
x
x
Value Expression All Concatenation+ x
Concatenation
x
x
x
x
x x
x
x
≠ ≠ ≠
÷ ÷ ÷
Product Description
Description
Products
A statement that provides pertinent details about the product. This information is useful to our sales and promotion efforts and is provided to our customers by means of various promotional materials.
Alphanumeric
180
None x
x
x .Keyboard ( , / $ # %)
FIELD SPECIFICATIONS
–
–
–
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valid for the field, so you decide to specify a general range of values for
now. Figure 9.12 shows the revised logical elements for the CATEGORY field.
You’ll revisit this field (and its elements) again when you establish busi-
ness rules for the database. With this problem solved, your meeting—as
well as the process of establishing field specifications—is complete.
Summary
The chapter opened with an explanation of why field specifications are
important and the benefits you derive from defining them. You learned
Figure 9.12. The logical elements for the CATEGORY field in the PRODUCTS table.
Logical Elements
Key Structure:
Non
Not Determined At This Time
Edit Rule:
Null Support: Nulls Allowed
Enter Now, Edits Allowed
Enter Now, Edits Not Allowed
Enter Later, Edits Allowed
Primary
AlternateForeign
No Nulls
Uniqueness: Non-unique Unique
Required Value: No Yes
Comparisons Allowed:
x
x
x
Range of Values:
Default Value:
Values Entered By: User
Operations Allowed:
System
Key Type:
CompositeSimple
x
Enter Later, Edits Not Allowed
<> <=>=
Other Fields
Same Field =
Value Expressionx <> <=>==
<> <=>==x
All
All
All
Same Field
Other Fields Concatenation
All
All
+
+
x
x
Value Expression All Concatenation+ x
Concatenation
Any valid internal or external product category.
≠ ≠ ≠
÷ ÷ ÷
x
x
x
x x
x –
–
–
From the Library of Stephen Benoit
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Summary 319
that defining specifications helps you establish and enforce field-level
integrity, enhances overall data integrity, and compels you to acquire a
complete understanding of the nature and purpose of the data in the
database. This level of understanding enables you to leverage the data
to your best advantage.
Next, we discussed the anatomy of a field specification. You’re now fa-
miliar with the three categories of elements within the specification and
the sheet you use to record them. We then discussed each category and
its elements in detail. As you now know, the General Elements category
represents the most basic attributes of the field. During this discussion,
you learned a set of guidelines that will help you compose a good field
description. You also learned that you could define three types of speci-
fications, thus enabling you to establish and maintain consistent field
definitions. We examined the Physical Elements category next, and you
learned that it pertains to the structure of the field. The Logical Ele-
ments category was the last topic of discussion in this section. You now
know that it mainly pertains to a field’s values and that it includes ele-
ments such as Key Type, Null Support, Range of Values, Edit Rule,
Comparisons Allowed, and Operations Allowed.
We then discussed how to use each type of specification, and you
learned a set of guidelines that will help you determine which one to de-
fine for a given field. You also examined samples of the specifications,
and you know how they differ.
The chapter ended with a discussion of defining field specifications for
each field. Here you learned that the best way to ensure complete and
accurate specifications is to work with users and management to define
them. You should first define as many specifications as you can and
then work with the staff to define specifications for the remaining fields.
You also learned that you could work with staff to refine the specifica-
tions you initially defined.
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Review Questions
1. State two major reasons why field specifications are important.
2. What do you gain by establishing field-level integrity?
3. What are the three categories of elements in a field specification?
4. Name the three types of specifications.
5. Why is it beneficial for you to compose a proper field description?
6. What does the Data Type element indicate?
7. What does the Character Support element indicate?
8. What is the purpose of the Display Format element?
9. What types of keys are indicated on a field specification?
10. True or False: A null represents a blank value.
11. What is the significance of the Range of Values element?
12. What is the purpose of an Edit Rule?
13. What is the purpose of the Comparisons Allowed element?
14. What is a value expression?
15. When do you use a generic specification?
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10 Table Relationships
There is no substitute for the comfort supplied by the utterly taken-for-granted relationship.
—IRIS MURDOCH
Topics Covered in This Chapter
Why Relationships Are Important
Types of Relationships
Identifying Existing Relationships
Establishing Each Relationship
Refining All Foreign Keys
Establishing Relationship Characteristics
Relationship-Level Integrity
Case Study
Summary
Review Questions
You learned in Chapter 3 that a relationship exists between two tables
when you can in some way associate the records of the first table with
those of the second. You also learned that each relationship has three
distinct characteristics: the type of relationship that exists between the
tables, the manner in which each participates, and the degree to which
each table participates.
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322 Chapter 10 Table Relationships
In this chapter, I’ll discuss these topics in more detail. You’ll first learn
how to identify and establish the relationships between the tables in a
database and then how to set each relationship’s characteristics. You’ll
also learn how to diagram tables and relationships, which will enable
you to create a graphic representation of the entire database structure.
Why Relationships Are Important
A relationship is an important component of a relational database.
• It establishes a connection between a pair of tables that are logi-
cally related to each other. A pair of tables is logically related via
the data each contains. For example, consider the tables in
Figure 10.1.
A logical relationship exists between the data in the STUDENTS
table and the data in the STUDENT INSTRUMENTS table. A stu-
dent can check out one or more instruments during the course of
a school year, so a record in the STUDENTS table (representing
the student) can be related to one or more records in the STU-
DENT INSTRUMENTS table (representing the particular instru-
ments the student checks out).
Figure 10.1. A pair of logically related tables.
StudLast Name
Ehrlich
McLain
Rosales
StudFirst Name
Zachary
Susan
Joe
Student ID
60001
60002
60003
Students
<< other fields >>
......
......
......
ChowMichael60004 ......
ThompsonAngie60005 ......
Student Instruments
Student ID
60002
60003
60001
Checkout Date
09/26/01
09/28/01
09/28/01
Instrument ID
1000
1002
1010
60003 09/28/011013
60003 09/28/011011
60001
60001
10/02/01
10/02/01
1022
1021
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Types of Relationships 323
• It helps to further refine table structures and minimize redundant
data. As you establish a relationship between a pair of tables, you
will inevitably make minor modifications to the table structures.
These refinements will make the structures more efficient and
minimize any redundant data that the tables may contain.
• It is the mechanism that enables you to draw data from multiple
tables simultaneously. In Chapter 12, you’ll learn how a relation-
ship enables you to construct a view using fields from two or more
related tables.
A properly defined relationship ensures relationship-level integrity, which
guarantees that the relationship itself is reliable and sound. (Recall that
relationship-level integrity is a component of overall data integrity.) You
can take advantage of the many benefits a relational database provides
only when you establish each relationship carefully and properly. Failure
to do so means that you’ll have a hard and tedious time working with
data from multiple tables, and you’ll certanly encounter problems when
you try to insert, update, or delete records in related tables. You’ll learn
more about these types of problems later as the design process unfolds.
Types of Relationships
Before you begin to establish relationships between tables in the data-
base, you must know what types of relationships can exist between a
given pair of tables. Knowing how to identify them properly is an invalu-
able skill for designing a database successfully.
There are three specific types of relationships that can exist between a
pair of tables: one-to-one, one-to-many, and many-to-many. The tables
participate in only one type of relationship at any given time. (You’ll
rarely need to change the type of relationship between a pair of tables.
Only major changes in either of the table’s structures could cause you
to change the relationship.)
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324 Chapter 10 Table Relationships
One-to-One Relationships
A pair of tables bears a one-to-one relationship when a single record in
the first table is related to only one record in the second table, and a
single record in the second table is related to only one record in the first
table. Figure 10.3 shows a generic example of a one-to-one relationship.
❖ Note The discussion for each type of relationship begins with a generic example of the relationship. Learning how to visualize a
relationship generically enables you to understand the principle
behind the relationship itself. Once you understand how and why
the relationship works, you’ll be able to determine whether it ex-
ists between a given pair of tables quite easily.
Each discussion also includes an example of how to diagram the
relationship. I provide special instructions pertaining to the
diagramming process where appropriate and explain the symbols
incorporated within the diagram as necessary. This allows you to
learn the diagramming method at a reasonable pace and keeps
you from having to memorize the entire set of diagram symbols all
at once.
Figure 10.2 shows the first symbols you will use to diagram a
table relationship.
Figure 10.2. Diagramming symbols for a data table and a subset table.
Table Name
Subset TableData Table
Table Name
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Types of Relationships 325
As you can see, a single record in TABLE A is related to only one record
in TABLE B, and a single record in TABLE B is related to only one record
in TABLE A. A one-to-one relationship usually (but not always) involves
a subset table. Figure 10.4 shows an example of a typical one-to-one re-
lationship that you might find in a database for an organization’s human
resources department. This example also illustrates a situation where
neither of the tables is a subset table.
Figure 10.3. A generic example of a one-to-one relationship.
Table A Table B
Figure 10.4. A typical example of a one-to-one relationship.
Employees
Compensation
Home Phone
553-3992
790-3992
551-4993
EmpLast Name
Erlich
McLain
Rosales
EmpFirst Name
Zachary
Susan
Joe
EmpID
100
101
102
<< other fields >>
......
......
......
EmpID
100
101
102
Commission Rate
5.0%
3.5%
5.0%
Hourly Rate
25.00
19.75
22.50
<< other fields >>
......
......
......
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326 Chapter 10 Table Relationships
Although the fields in these tables could be combined into a single ta-
ble, the database designer chose to place the fields that can be viewed
by anyone in the organization in the EMPLOYEES table and the fields
that can be viewed only by authorized personnel in the COMPENSA-
TION table. Only one record is required to store the compensation data
for a given employee, so there is a distinct one-to-one relationship be-
tween a record in the EMPLOYEES table and a record in the COMPEN-
SATION table.
A one-to-one relationship usually (but not always) involves a subset ta-
ble. (Indeed, neither of the tables in Figure 10.4 is a subset table.) Fig-
ure 10.5 shows a generic example of how you create a relationship
diagram for a one-to-one relationship.
The line that appears between the tables in the diagram indicates the
type of relationship, and there is a particular line that you use for each
type. Later in this chapter, you’ll learn how to modify the line to show
the characteristics of the relationship as well. Figure 10.6 shows the re-
lationship diagram for the EMPLOYEES and COMPENSATION tables in
Figure 10.4. (Note that a Data Table symbol represents each table.)
Figure 10.5. Diagramming a one-to-one relationship.
Table NameTable Name
This line indicates that a single record in TABLE B is related to only one record in TABLE A.
This line indicates that a single record in TABLE A is related to only one record in TABLE B,
From the Library of Stephen Benoit
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Types of Relationships 327
One-to-Many Relationships
A one-to-many relationship exists between a pair of tables when a single
record in the first table can be related to one or more records in the sec-
ond table, but a single record in the second table can be related to only
one record in the first table. Let’s look at a generic example of this type
of relationship.
Say you’re working with two tables, TABLE A and TABLE B, that have a
one-to-many relationship between them. Because of the relationship, a
single record in TABLE A can be related to one or more records in TABLE B.
Figure 10.7 shows the relationship from the perspective of TABLE A.
Conversely, a single record in the TABLE B can be related to only one
record in TABLE A. Figure 10.8 shows the relationship from the per-
spective of TABLE B.
Figure 10.6. The relationship diagram for the EMPLOYEES and COMPENSATION tables.
Employees Compensation
Figure 10.7. A one-to-many relationship from the perspective of TABLE A.
Table A Table B
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328 Chapter 10 Table Relationships
This is by far the most common relationship that exists between a pair
of tables in a database, and it is the easiest to identify. It is crucial from
a data-integrity standpoint because it helps to eliminate duplicate data
and to keep redundant data to an absolute minimum. Figure 10.9
shows a common example of a one-to-many relationship that you might
find in a database for a video rental store.
A customer can check out any number of videos, so a single record in
the CUSTOMERS table can be related to one or more records in the
CUSTOMER RENTALS table. A single video, however, is associated with
only one customer at any given time, so a single record in the CUS-
Figure 10.8. A one-to-many relationship from the perspective of TABLE B.
Table A Table B
Figure 10.9. A typical example of a one-to-many relationship.
CustLast Name
Litwin
Balter
Baron
CustFirst Name
Paul
Alison
Andy
Customer ID
9001
9002
9003
Customers
......
......
......
KunickiChris9004 ......
ChipmanMary9005 ......
Customer Rentals
Customer ID
9002
9003
9001
Checkout Date
09/26/01
09/28/01
09/28/01
Video ID
80115
64558
10202
9003 09/28/0111354
9003 10/02/0178422
9005
9004
09/26/01
10/05/01
30556
20655
<< other fields >>
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Types of Relationships 329
TOMER RENTALS table is related to only one record in the CUSTOM-
ERS table.
Figure 10.10 shows a generic example of how you create a relationship
diagram for a one-to-many relationship.
Note that the crow’s foot symbol is always located next to the table on
the “many” side of the relationship. Figure 10.11 shows the relationship
diagram for the CUSTOMERS and CUSTOMER RENTALS tables in Fig-
ure 10.9.
Figure 10.10. Diagramming a one-to-many relationship.
Table A
This line indicates that a single record in TABLE B is related to only one record in TABLE A.
This “crow’s foot” indicates that a single record in TABLE A is related
to many records in TABLE B.
Table B
Figure 10.11. The relationship diagram for the CUSTOMERS and CUSTOMER RENTALS tables.
Customers Customer Rentals
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330 Chapter 10 Table Relationships
Many-to-Many Relationships
A pair of tables bears a many-to-many relationship when a single record
in the first table can be related to one or more records in the second ta-
ble and a single record in the second table can be related to one or more
records in the first table.
Assume once again that you’re working with TABLE A and TABLE B
and that there is a many-to-many relationship between them. Because
of the relationship, a single record in TABLE A can be related to one or
more records (but not necessarily all) in TABLE B. Conversely, a single
record in the TABLE B can be related to one or more records (but not
necessarily all) in TABLE A. Figure 10.12 shows the relationship from
the perspective of each table.
This is the second most common relationship that exists between a pair
of tables in a database. It can be a little more difficult to identify than a
Figure 10.12. A many-to-many relationship from the perspective of both TABLE A and TABLE B.
Table A Table B
Table A Table B
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Types of Relationships 331
one-to-many relationship, so you must be sure to examine the tables
carefully. Figure 10.13 shows a typical example of a many-to-many re-
lationship that you might find in a school database, which happens to
be a classic example of this type of relationship (no pun intended!).
A student can attend one or more classes during a school year, so a sin-
gle record in the STUDENTS table can be related to one or more records
in the CLASSES table. Conversely, one or more students will attend a
given class, so a single record in the CLASSES table can be related to
one or more records in the STUDENTS table.
Figure 10.14 shows a generic example of how you create a relationship
diagram for a many-to-many relationship.
Figure 10.13. A typical example of a many-to-many relationship.
Introduction to Political Science 5900009 Political Science 220337 ......3308
Class NameClass ID
900001
900002
900003
Instructor ID
220087
220039
220148
Classes
<< other fields >>
......
......
......
Credits
3
5
2
Classroom
2201
7012
3305
Advanced Music Theory
Computers in Business
American History
Computers in Society
Introduction to Database Design
Advanced Calculus
Introduction to Biology
Introduction to Physics
2
4
5
5
5
900004
900005
900006
900007
900008
Computer Science
Math
Music
History
Physics
Computer Science
Biology
Computer Science
Class Category
220387
220387
220498
......
......
......
5115
5117
3112
220516
220087
......
......
5105
2205
<< other fields >>
......
......
......
StudState
WA
WA
WA
WA
WA
StudStreet Address
1204 Bryant Road
201 Cherry Lane SE
4141 Lake City Way
2100 Mineola Avenue
101 C Street, Apt. 32
StudCity
Seattle
Redmond
Woodinville
Bellevue
Redmond
StudZipcode
98125
98052
98073
StudLast Name
Erlich
McLain
Rosales
StudFirst Name
Zachary
Susan
Joe
Student ID
60001
60002
60003
Students
BarletDiana60004
WickerathTom60005
98072
98006
......
......
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332 Chapter 10 Table Relationships
In this case, there is a crow’s foot symbol located next to each table. Fig-
ure 10.15 shows the relationship diagram for the STUDENTS and
CLASSES tables in Figure 10.13.
Problems with Many-to-Many Relationships
A many-to-many relationship has an inherent peculiarity that you must
address before you can effectively use the data from the tables involved
in the relationship. The issue is this: How do you easily associate
records from the first table with records in the second table in order to
Figure 10.14. Diagramming a many-to-many relationship.
Table A
This crow’s foot indicates that a single record in TABLE B is related to
many records in TABLE A.
This crow’s foot indicates that a single record in TABLE A is related to
many records in TABLE B.
Table B
Figure 10.15. The relationship diagram for the STUDENTS and CLASSES tables.
Students Classes
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Types of Relationships 333
establish the relationship? This is an important question because you’ll
encounter problems such as these if you do not establish the relation-
ship properly:
• It will be tedious and somewhat difficult to retrieve information
from one of the tables.
• One of the tables will contain a large amount of redundant data.
• Duplicate data will exist within both tables.
• It will be difficult for you to insert, update, and delete data.
There are two common methods that novice and inexperienced develop-
ers use in a futile attempt to address this situation. I’ll demonstrate how
you might apply these methods using the STUDENTS and CLASSES ta-
bles in Figure 10.16 as examples.
Figure 10.16. Structures of the STUDENTS and CLASSES tables.
Table Structures
ClassesStudents
Class NameStudFirst Name
ClassroomStudState
Class CategoryStudLast Name
CreditsStudStreet Address
Instructor IDStudCity
Class DescriptionStudZipcode
Class ID PKStudent ID PK
Catalog CodeStudHome Phone
Social Security Number
StudEmail Address
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334 Chapter 10 Table Relationships
As you can see, there is no actual connection between the two tables, so
you have no way of associating records in one table with records in the
other table. The first method you might use to attempt to establish a
connection involves taking a field from one table and incorporating it a
given number of times within the other table. (This approach usually
appeals to people who are accustomed to working with spreadsheets.)
For example, you could take the STUDENT ID field from the STUDENTS
table and incorporate it within the CLASSES table structure, creating as
many copies of the field as you need to represent the maximum number
of students that could attend any class. Figure 10.17 shows the revised
version of the CLASSES table structure.
❖Note As this example unfolds, keep in mind that every many-to- many relationship you encounter will exhibit these same issues.
Figure 10.17. Incorporating STUDENT ID fields within the CLASSES table structure.
Table Structures
Student ID 22Student ID 14Student ID 6
Student ID 17Student ID 9Student ID 1Class ID PK
Student ID 21Student ID 13Student ID 5Instructor ID
Student ID 18Student ID 10Student ID 2Class Name
Student ID 23Student ID 15Student ID 7Class Description
Classes
Student ID 19Student ID 11Student ID 3Class Category
Student ID 20Student ID 12Student ID 4Credits
Classroom
Student ID 24Student ID 16Student ID 8Catalog Code
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Types of Relationships 335
This structure is likely to be problematic, so you might try taking the
CLASS ID field from the CLASSES table and incorporating it within the
STUDENTS table structure instead. Figure 10.18 shows the revised ver-
sion of the STUDENTS table structure.
Do these structures look (vaguely) familiar? They should. All you’ve
done using this method is introduce a “flattened” multivalued field into
the table structure. In doing so, you’ve also introduced the problems as-
sociated with a multivalued field. (If necessary, review Chapter 7.) Al-
though you know how to resolve a multivalued field, this is not a good
or proper way to establish the relationship.
The second method you might attempt to use is simply a variation of the
first method. In this case, you take one or more fields from one table
and incorporate a single instance of each field within the other table. For
Figure 10.18. Incorporating CLASS ID fields within the STUDENTS table structure.
Table Structures
Students
Social Security Number
StudEmail Address
Student ID PK Class ID 1
StudFirst Name Class ID 2
StudLast Name Class ID 3
StudStreet Address Class ID 4
StudCity Class ID 5
StudState Class ID 6
StudZipcode Class ID 7
StudHome Phone Class ID 8
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336 Chapter 10 Table Relationships
example, you could take the CLASS ID, CLASS NAME, and INSTRUCTOR ID fields
from the CLASSES table and incorporate them into the STUDENTS table
in order to identify the classes in which a student is currently enrolled.
This may seem to be a distinct improvement over the first method, but
you’ll see that there are problems that arise from such modifications
when you load the revised STUDENTS table with sample data.
Figure 10.19 clearly illustrates the problems you’ll encounter using this
method.
• The table contains unnecessary duplicate fields. You learned all
about unnecessary duplicate fields and the problems they pose
back in Chapter 7, so you know that using them here is not a
good idea. Besides, it is very likely that the CLASS NAME and IN-
STRUCTOR ID fields are not appropriate in the STUDENTS table—
the CLASS ID field identifies the class sufficiently, and it is really all
you need to identify the classes a student is taking.
Figure 10.19. The revised STUDENTS table with sample data.
Student Last NameStudent First NameStudent ID
Students
Class NameClass ID Instructor ID << other fields >>
ErlichZachary60001
ErlichZachary60001
ErlichZachary60001
ErlichZachary60001
Introduction to Political Science900009 220087 ......
Advanced Music Theory
Computers in Business
900002
900004
220039
220121
......
......
American History900003 220148 ......
McLainSusan60002
McLainSusan60002
McLainSusan60002
Advanced Music Theory900002 220039 ......
Introduction to Political Science900009 220087 ......
Introduction to Biology900006 220117 ......
RosalesJoe60003 Computers in Business900004 220121 ......
RosalesJoe60003 Advanced Calculus900001 220101 ......
RosalesJoe60003 Introduction to Physics900008 220075 ......
BarletDiana60004 Introduction to Database Design900007 220120 ......
From the Library of Stephen Benoit
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Types of Relationships 337
• There is a large amount of redundant data. Even if you remove the
CLASS NAME and INSTRUCTOR ID fields from the STUDENTS table, the
CLASS ID field will still produce a lot of redundant data.
• It is difficult to insert a new record. If you enter a record in the
STUDENTS table for a new class (instead of entering it in the
CLASSES table) without also entering student data, the fields per-
taining to the student will be null—including the primary key of
the STUDENTS table (STUDENT ID). This will automatically trigger a
violation of the Elements of a Primary Key because the primary
key cannot be null; therefore, you cannot insert the record into
the table until you can provide a proper primary key value.
• It is difficult to delete a record. This is especially true if the only data
about a new class has been recorded in the particular student
record you want to delete. Note the record for Diana Barlet, for
example. If Diana decides not to attend any classes this year and
you delete her record, you will lose the data for the “Introduction to
Database Design” class. That might not create a serious problem—
unless someone neglected to enter the data about this class into
the CLASSES table as well. Once you delete Diana’s record, you’ll
have to re-enter all of the data for the class in the CLASSES table.
Fortunately, you will not have to worry about any of these problems be-
cause you’re going to learn the proper way to establish a many-to-many
relationship.
Self-Referencing Relationships
This particular type of relationship does not exist between a pair of ta-
bles, which is why it isn’t mentioned at the beginning of this section. It
is instead a relationship that exists between the records within a table.
Ironically, you’ll still regard this throughout the design process as a ta-
ble relationship.
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338 Chapter 10 Table Relationships
A table bears a self-referencing relationship (also known as a recursive
relationship) to itself when a given record in the table is related to other
records within the table. Similar to its dual-table counterpart, a self-
referencing relationship can be one-to-one, one-to-many, or many-to-
many.
One-to-One
A self-referencing one-to-one relationship exists when a given record in
the table can be related to only one other record within the table. The
MEMBERS table in Figure 10.20 is an example of a table with this type
of relationship. In this case, a given member can sponsor only one other
member within the organization; the SPONSOR ID field stores the member
identification number of the member acting as a sponsor. Note that Su-
san McLain is Tom Wickerath’s sponsor.
Figure 10.21 shows how you diagram this type of relationship.
One-to-Many
A table bears a self-referencing one-to-many relationship to itself when a
given record in the table can be related to one or more other records
within the table. Figure 10.22 shows an example in which a given cus-
tomer can refer other customers to the organization. The REFERRED BY
Figure 10.20. Example of a self-referencing one-to-one relationship.
<< other fields >>
......
......
......
MbrLast Name
Erlich
McLain
Rosales
MbrFirst Name
Zachary
Susan
Joe
Member ID
1001
1002
1003
Members
BarletDiana1004
WickerathTom1005
......
......
Sponsor ID
1001
1003
1002
From the Library of Stephen Benoit
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Types of Relationships 339
field stores the customer identification number of the customer making
the referral. Note that Paul Litwin referred both Andy Baron and Mary
Chipman.
Figure 10.23 shows how you diagram a self-referencing one-to-many
relationship.
Many-to-Many
A self-referencing many-to-many relationship exists when a given record
in the table can be related to one or more other records within the table
and one or more records can themselves be related to the given record.
Figure 10.21. Diagramming a self-referencing one-to-one relationship.
The line on the side of the table shows the self- referencing (or “recursive”) nature of the relationship
and also indicates the relationship type.
Members
Figure 10.22. Example of a self-referencing one-to-many relationship.
CustLast Name
Litwin
Balter
Baron
CustFirst Name
Paul
Alison
Andy
Customer ID
9001
9002
9003
Customers
<< other fields >>
......
......
......
KunickiChris9004 ......
ChipmanMary9005 ......
Referred By
9001
9003
9001
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340 Chapter 10 Table Relationships
This may sound somewhat confusing at first, but the example in
Figure 10.24 should help clarify the matter.
In this case, a particular part can comprise several different component
parts, and it can itself be a component of other parts. For example, a
clamp assembly (Part ID 704) is composed of a fastening bolt (Part ID
703), a bottom clamp (Part ID 702), and a top clamp (Part ID 701). Addi-
tionally, the clamp assembly is itself a component of a seat assembly
(Part ID 707) and a frame assembly (Part ID 711). Figure 10.25 shows
how you diagram this type of relationship.
Figure 10.23. Diagramming a self-referencing one-to-many relationship.
Customers
Figure 10.24. Example of a self-referencing many-to-many relationship.
Part NamePart ID
Parts
<< other fields >>
701 Top Clamp
702
......
Bottom Clamp
703
......
Fastening Bolt
704
......
Seat Assembly
705
......
Saddle
706
......
Seatpost
707
......
Frame Assembly
708
......
Body Tube
709
......
Front Fork Tube
710
......
Rear Stay Tube ......
711
Clamp Assembly ......
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Identifying Existing Relationships 341
Now that you’ve learned about the various types of table relationships,
your next task is to identify the relationships that currently exist among
the tables in the database.
Identifying Existing Relationships
When you were composing the table descriptions earlier in the database-
design process (back in Chapter 7, to be exact), you assembled a
❖ Note Before you begin to work through the examples in the re- mainder of the chapter, now is a good time to remember a princi-
ple I presented in the introduction:
Focus on the concept or technique and its intended
results, not on the example used to illustrate it.
There are, without a doubt, any number of ways in which you can
relate the tables in these examples (and in the case study as well),
depending on each table’s role within a given database. The
manner in which I use the examples here is not important; what
is important are the techniques I use to identify and establish
relationships between tables. Once you learn these techniques,
you can identify and establish relationships for any pair of tables
within any context you may encounter.
Figure 10.25. Diagramming a self-referencing many-to-many relationship.
Parts
From the Library of Stephen Benoit
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342 Chapter 10 Table Relationships
representative group of users and management to help you with that
task. These people were also designated as representatives of the orga-
nization and granted the authority to aid in the decision-making pro-
cess throughout the remainder of the database-design process. (At
least, this is the current assumption for the sake of discussion and ex-
ample.) Now you’ll arrange meetings with this group once again so that
they can help you identify existing table relationships. These folks can
provide valuable input because they are likely to have a good perspec-
tive on how various subjects (or tables) are related. Although their per-
ceptions of the manner in which these subjects are related may not
always be complete or accurate, their contributions will still be useful in
identifying most of the relationships.
Begin the process of identifying relationships by creating a matrix of all
the tables in your database. (You can do this on a sheet of paper, a
white board, or a spreadsheet program.) For example, assume you’re
working with these tables:
List each of the tables across the top of the matrix, and then again down
the left-hand side of the matrix; make certain the table names are in the
same order. Figure 10.26 illustrates how the matrix should appear.
Select a table on the left as a starting point and determine whether it
has a relationship with any of the tables listed across the top, working
your way through the matrix as you do so. (It doesn’t matter whether
you work your way across the top or down the side. Just make sure you
work consistently, as it will make the task much easier.)
Keep in mind that you’re looking for direct relationships only—there
must be a specific connection between tables participating in the rela-
BUILDINGS
CLASSES
COMPENSATION
FACULTY
ROOMS
STAFF
STUDENTS
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Identifying Existing Relationships 343
tionship. For example, the CLASSES table has a direct relationship to
the STUDENTS table because one or more students can attend a given
class. Conversely, the CLASSES table has an indirect relationship to the
STAFF table via the FACULTY table; it is a faculty member that teaches
a class, not a staff member. (You don’t have to worry about indirect rela-
tionships just yet.)
As you work with a pair of tables, ask the participants questions about
the records in each table. Your goal is to determine the relationship be-
tween a single record in one table to one or more records in the other ta-
ble, and vice versa. (Remember that each record represents a single
instance of the subject represented by the table.) When you get to a
point where you’re examining the same table on both sides of the ma-
trix, try to determine the relationship between a given record in the ta-
ble to one or more other records within the table.
There are two types of questions you can ask:
1. Associative. This is a simple and straightforward type of question
that you can generically phrase as follows: Can a single record in
(name of first table) be associated with one or more records in
Figure 10.26. Setting up a table matrix to help identify existing relationships.
Buildings
Classes
Compensation
Faculty
Rooms
Staff
Students
Buildings Classes Compensation Faculty Rooms Staff Students
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344 Chapter 10 Table Relationships
(name of second table)? Considering the matrix in Figure 10.26,
you might ask an associative question such as this:
Can a single record in CLASSES be associated with one or more
records in BUILDINGS?
You can use this type of question to determine whether a table
has a self-referencing relationship by making two minor modifica-
tions to the question itself: Can a single (singular form of the table
name) be associated with one or more (plural form of the table
name)? For example, here’s a question you might pose for the
STAFF table:
Can a single staff member be associated with one or more other
staff members?
2. Contextual. This type of question contrasts a single instance of the
subject represented by the first table against multiple instances of
the subject represented by the second table. There are two catego-
ries within this type of question: ownership-oriented and action-
oriented.
a. Ownership-oriented questions include words or phrases such
as “own,” “has,” “is part of,” and “contain.” Here’s an example of
this type of question:
Can a single order contain one or more products?
You can use this question to test for a self-referencing relation-
ship by making the same modifications you made to the
associative question. Here’s an example of a question you might
pose for a PARTS table:
Can a single part contain one or more other parts?
b. Action-oriented questions incorporate action verbs such as
“make,” “visit,” “place,” “teach,” and “attend.” Here’s an exam-
ple of this type of question:
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Identifying Existing Relationships 345
Does a single flight instructor teach one or more types of
classes?
As you may have already guessed, you can use this question to
test for a self-referencing relationship as well by making the
same modifications:
Does a single staff member manage one or more other staff
members?
Use the type of question you believe to be the most appropriate for the
pair of tables you’re working with. As you work down the list of tables in
the matrix, you’ll eventually realize that you’re asking questions about a
given pair of tables twice—once from the perspective of the first table
and then again from the perspective of the second table. The answers to
both of these questions will identify the type of relationship that exists
between the tables.
Continuing with the example, assume that you’ve decided to start with
the CLASSES table and this is your first question:
Is a single class held in one or more buildings?
The answer to this question will reveal the type of relationship that ex-
ists between these tables from the perspective of the CLASSES table. If
you receive the following answer, then a one-to-one relationship exists
between these tables:
A single class is held in only one building.
If you receive this answer, however, then a one-to-many relationship ex-
ists between the two tables:
A single class may be held in more than one building.
Once you’ve identified the relationship, indicate the relationship type in
the box located at the junction of the CLASSES table row (on the left)
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346 Chapter 10 Table Relationships
and the BUILDINGS table column (on the top). You can use the follow-
ing shorthand symbols for the relationship types:
1:1—one-to-one
1:N—one-to-many
M:N—many-to-many
Figure 10.27 shows how the table matrix looks after you’ve finished
identifying relationships for the CLASSES table. Remember that the rela-
tionships indicated here are from the perspective of the CLASSES table.
You’ve probably noticed that some of the junction boxes are empty; this
is perfectly acceptable. It’s unnecessary for you to enter anything into
the junction box if there is no relationship between the tables at either
end of the junction.
❖ Note You won’t need the many-to-many shorthand symbol at this point, but I’ve included it here for completeness.
Figure 10.27. Completed table-matrix entries for the CLASSES table.
Buildings
Classes
Compensation
Faculty
Rooms
Staff
Students
Buildings Classes Compensation Faculty Rooms Staff Students
1:1 1:N 1:1 1:N
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Identifying Existing Relationships 347
Now you repeat this process for each table on the left-hand side of the
matrix. Remember that you can start with any table. Let’s assume that
you decide to continue with the BUILDINGS table, and you’re attempt-
ing to identify the relationship between it and the CLASSES table. Yes, I
know you’ve covered this once already, but in this case you’re identify-
ing the relationship from the perspective of the BUILDINGS table. Let’s
now assume that you ask this question:
Does a single building provide space for more than one class?
If the answer is yes, then a one-to-many relationship exists between
these tables; otherwise, it’s a one-to-one relationship. Once you’ve iden-
tified the relationship, indicate the relationship type in the box located
at the junction of the BUILDINGS table row (on the left) and the
CLASSES table column (on the top). Figure 10.28 shows the revised ta-
ble matrix with your entries for the BUILDINGS table.
You’ve just seen two examples of how to identify a relationship be-
tween a distinct pair of tables, so let’s take a look at how you identify a
self-referencing relationship for a single table. Assume you’re working
with the STAFF table, and you’re now at the junction between the
STAFF table on the left and the STAFF table on the top. Using the
Figure 10.28. Completed table-matrix entries for the BUILDINGS table.
Buildings
Classes
Compensation
Faculty
Rooms
Staff
Students
Buildings Classes Compensation Faculty Rooms Staff Students
1:1 1:N 1:1 1:N
1:N 1:N
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348 Chapter 10 Table Relationships
techniques you learned earlier in this section, you might pose a ques-
tion such as this:
Can a single staff member be associated with one or more other
staff members?
As with the earlier examples, the answer will indicate the type of rela-
tionship. Say you received this answer:
Yes, a given staff member can be the spouse of another staff
member.
This indicates (rather obviously) that a self-referencing one-to-one rela-
tionship exists for the STAFF table. But assume you received this an-
swer instead:
Yes, a single staff member can manage several other staff
members.
You probably quickly realized that this answer indicates that a self-
referencing one-to-many relationship exists for the STAFF table. Identi-
fying these two types of relationships is a relatively easy task; identify-
ing a self-referencing many-to-many relationship can be slightly more
difficult.
This is the type of question you must ask in order to determine whether
a table has a self-referencing many-to-many relationship: Can a single
(singular form of the table name) be associated with one or more other
(plural form of the table name), and can any of those (plural form of the
table name) then be associated with yet one or more other (plural form of
the table name)? For example, here’s a question you might pose for the
STAFF table:
Can a single staff member be associated with one or more other
staff members, and can any one of those staff members then be
associated with one or more other staff members?
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Identifying Existing Relationships 349
An answer such as the following (or one very similar to it) indicates that
the STAFF table has a self-referencing many-to-many relationship:
Yes, a given staff member can manage several other staff mem-
bers, and any one of those folks can then supervise one or more
other staff members.
Once you’ve identified the type of self-referencing relationship that ex-
ists for the table, you indicate it in the table matrix as you would any
other relationship.
Relationships will often differ from one perspective to the other, and you
must know how to determine what type of relationship officially exists
between each pair of tables on the matrix. You make this determination
using the following set of formulas; each formula corresponds to a par-
ticular relationship type definition. (I’ve provided the definitions as a
point of reference.)
1:1 + 1:1 = 1:1 A pair of tables bears a one-to-one relationship when a single record in the first table is related
to only one record in the second table, and a sin-
gle record in the second table is related to only
one record in the first table.
1:N + 1:1 = 1:N A one-to-many relationship exists between a pair of tables when a single record in the first table
can be related to one or more records in the sec-
ond table, but a single record in the second ta-
ble can be related to only one record in the first
table.
1:N + 1:N = M:N A pair of tables bears a many-to-many relation- ship when a single record in the first table can be
related to one or more records in the second ta-
ble and a single record in the second table can be
related to one or more records in the first table.
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350 Chapter 10 Table Relationships
Here is the specific procedure you’ll use to identify the official relation-
ship between a pair of tables in the matrix. (It incorporates the relation-
ship formulas above.) Let’s first look at a generic version of the
procedure.
1. Select a pair of tables and note the entry at the junction between
the first table and the second table.
2. Locate the second table on the same side of the matrix you’re
working on and note the entry at the junction between it and the
first table on the opposite side of the matrix.
3. Apply the appropriate formula to the two entries and identify the
official relationship between the tables.
4. Diagram the relationship in the appropriate manner.
5. Cross out both entries on the matrix.
Now, let’s take a look at how you apply this procedure to a pair of tables
in the matrix. (In this example, you’re working down the left-hand side
of the matrix.)
1. Assume you’ve selected the BUILDINGS and CLASSES tables. You
note that the entry at the junction between BUILDINGS and
CLASSES is 1:N.
2. Now you proceed down the left-hand side of the matrix until you
locate the CLASSES table and then note that the entry at the junc-
tion between the CLASSES and BUILDINGS table is 1:1.
3. Using these entries with the appropriate formula, you determine
that the official relationship between the BUILDINGS and
CLASSES tables is 1:N. (1:N + 1:1 = 1:N)
4. You create a one-to-many relationship diagram for the BUILDINGS
and CLASSES tables.
5. You cross out the entries on the matrix.
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Identifying Existing Relationships 351
Figure 10.29 shows the results of your work.
Note that the relationship diagram is built from the perspective of the
BUILDINGS table. This is due to the fact that the BUILDINGS table is on
the “one” side of the relationship. When you create a simple diagram
such as this, I recommend that you always show the “one” side of the
relationship on the left and the “many” side on the right. Following this
practice will make your diagrams easy to read and help ensure that you
create them in a consistent manner. (This practice is unnecessary, how-
ever, when you create a complex diagram showing the relationships be-
tween several tables.)
At the very least, you should include each table’s primary key in the di-
agram. Doing so will prove to be a valuable visual aid when you begin to
establish the relationships. You could go so far as to display each table’s
Figure 10.29. Identifying the official relationship between the BUILDINGS and CLASSES tables.
Buildings
Classes
Compensation
Faculty
Rooms
Staff
Students
Buildings Classes Compensation Faculty Rooms Staff Students
1:1 1:N 1:1 1:N
1:N 1:N
1:1
1:N
1:N
1:N
1:1 1:1
1:1
1:1
1:N
Buildings Classes
Building Number PK Class ID PK
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352 Chapter 10 Table Relationships
complete structure (as you see in Figure 10.30), assuming you have
space on the diagram. Displaying the structures in this manner often
helps to reinforce the decision you’ve made regarding the type of rela-
tionship that exists between the tables. (I use both types of diagrams
throughout the remainder of the book.)
It’s worth mentioning that this procedure is much easier and shorter
when you work with a table that has a self-referencing relationship,
such as the STAFF table. As Figure 10.31 illustrates, all you have to do
here is diagram the relationship and cross out the entry on the matrix.
Continue this procedure until you’ve eliminated all of the entries on the
matrix. When you’ve finished identifying the official relationships
among the tables in the database, you can then go through the process
of establishing each relationship in the appropriate manner.
❖ Note You’ll occasionally find it difficult to identify the exact re- lationship between a given pair of tables. When this happens, just
load the tables with some sample data. This usually helps to re-
veal the type of relationship that exists between the tables.
Figure 10.30. Displaying each table’s structure in a relationship diagram.
Buildings Classes
Building Number PK Number of Floors Elevator Access Site Parking Available
Class ID PK
Instructor ID
Class Name
Class Description
Class Category Credits
Classroom
Catalog Code
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Establishing Each Relationship 353
Establishing Each Relationship
This process involves defining an explicit logical connection between a
pair of related tables. The type of relationship that exists between the
tables determines the manner in which you define the connection.
One-to-One and One-to-Many Relationships
You use a primary key and a foreign key to establish the connection be-
tween tables participating in a one-to-one or one-to-many relationship.
(You’ll learn the definition of a foreign key in just a moment.)
The One-to-One Relationship
In this type of relationship, one table serves as a parent table and the
other serves as a child table. A record must exist in the parent table
Figure 10.31. Working with a self-referencing relationship.
Staff
Buildings
Classes
Compensation
Faculty
Rooms
Staff
Students
Buildings Classes Compensation Faculty Rooms Staff Students
1:1 1:N 1:1 1:N
1:N 1:N
1:1
1:N
1:N
1:N
1:1 1:1
1:1
1:1
1:N
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354 Chapter 10 Table Relationships
before you can enter a related record in the child table; stated another
way, a record in the child table must have a related record in the par-
ent table. The roles you assign to the tables usually depend on the
subjects they represent, although there will be instances when you
can assign the roles rather arbitrarily. In Figure 10.32, for example,
you would most likely assign the parent role to the STAFF table and
the child role to the COMPENSATION table. This is a reasonable as-
sumption because it would be completely illogical to have a record
in the COMPENSATION table that is not related to a record in the
STAFF table.
In the case where one of the tables is a subset table, you will usually as-
sign the child role to the subset table. There are instances, however,
when you can assign the parent role to the subset table.
You establish a one-to-one relationship by taking a copy of the parent
table’s primary key and incorporating it within the structure of the child
table, where it then becomes a foreign key. (The term foreign key is de-
rived from the fact that the child table already has a primary key of its
own, and the primary key you are introducing from the parent table is
Figure 10.32. Which table would you pick as the parent table?
Staff Compensation
PK Staff ID Salary Amount Investment Plan Type Medical Plan Type Life Insurance Plan
Staff ID StaffFirst Name StaffLast Name StaffStreet Address StaffCity StaffState StaffZipcode StaffPhone Number Position Date Hired
PK
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Establishing Each Relationship 355
“foreign” to the child table.) In most one-to-one relationships, however,
the foreign key also serves as the child table’s primary key.
Figure 10.33 illustrates how you would establish the relationship be-
tween the STAFF and FACULTY tables. STAFF is the parent table in this
case because a record in the FACULTY table must be related to a record
in the STAFF table; faculty members are drawn from the school’s staff.
If you were to follow the procedure you just learned, you would take a
copy of the STAFF table’s primary key and incorporate it as a foreign
key in the FACULTY table. This is unnecessary, however, because FAC-
ULTY is already a properly defined subset table. (Recall that a subset ta-
ble and the data table from which it was derived must share the same
primary key. You learned how to define a subset table in Chapter 7 and
how to establish its primary key in Chapter 8.)
Figure 10.34 shows a slightly different example of a one-to-one relation-
ship. Assume that MANAGERS is a subset table of EMPLOYEES, but has
a direct relationship to DEPARTMENTS—a single manager is associated
with only one department, and a single department is associated with only
one manager. Further assume that MANAGERS is the parent table and
Figure 10.33. Establishing the one-to-one relationship between the STAFF and FACULTY tables.
Staff Faculty
PK Staff IDStaff ID StaffFirst Name StaffLast Name StaffStreet Address StaffCity StaffState StaffZipcode StaffPhone Number Position Date Hired
PK Title Status Tenured
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356 Chapter 10 Table Relationships
DEPARTMENTS is the child table. (This is a good example of a scenario in
which you can choose the roles rather arbitrarily. It’s also an instance of
when a subset table plays the parent role within the relationship.)
Establish the relationship between these tables using the procedure
you’ve just learned, and then identify the DEPARTMENTS table’s new
foreign key (EMPLOYEE ID) by placing the letters “FK” next to its name.
Figure 10.35 shows the revised relationship diagram with the results of
your modifications.
As long as you can visualize this process generically, you’ll be able to es-
tablish any one-to-one relationship you encounter.
Figure 10.34. A one-to-one relationship with a subset table in the parent role.
Managers Departments
PK
Email Address
Cellular Phone Number
Department ID
DeptName
Maximum Staff Level
DeptCategory
PKEmployee ID
Figure 10.35. Establishing the relationship between the MANAGERS and DEPARTMENTS tables.
Managers Departments
PK
Email Address
Cellular Phone Number
Department IDPKEmployee ID
DeptName
Maximum Staff Level
DeptCategory
Employee ID FK
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Establishing Each Relationship 357
There is a small change in the way you’ll diagram the relationships from
this point forward. You should now use the primary key as the begin-
ning point and the foreign key as the end point of the relationship line.
(The only exception will be when you’re diagramming the relationship
between a subset table and its parent data table.) Making this minor
modification will help you visualize the relationships more clearly and
make it easier to identify the fields that establish the relationship.
The One-to-Many Relationship
The technique you use to establish a one-to-many relationship is similar
to the one you used to establish a one-to-one relationship. You simply
❖ Note Many database designers will use MANAGER ID as the pri- mary key name in the MANAGERS table and the foreign key name
in the DEPARTMENTS table. I choose to use EMPLOYEE ID instead
for these reasons:
• MANAGERS is a subset of the EMPLOYEES table, so it
shares the same primary key (EMPLOYEE ID).
• It keeps the field in conformance with the Elements of the
Ideal Field. (It retains a majority of its characteristics when it
appears in more than one table.)
• It keeps the field in conformance with the Elements of a
Foreign Key. (You’ll learn about foreign keys later in this
chapter.)
• It removes any possible ambiguity or doubt about the true
nature of a foreign key. (I’ll explain this in more detail during
the discussion of the Elements of a Foreign Key.)
There is no absolute right or wrong way to do this—in the end, the
approach you use is simply a matter of style. Once you decide
which approach you want to use, however, make certain you use
it consistently.
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358 Chapter 10 Table Relationships
take a copy of the primary key from the table on the “one” side of the re-
lationship and incorporate it within the table structure on the “many”
side, where it then becomes a foreign key. For example, consider the
one-to-many relationship between the BUILDINGS and ROOMS tables
shown in Figure 10.36.
The relationship between these two tables is such that a single building
can contain one or more rooms, but a single room is contained within
only one building. Using the procedure above, you establish this rela-
tionship by taking a copy of the primary key (BUILDING NUMBER) from the
BUILDINGS table and incorporating it as a foreign key within the
ROOMS table. Now, revise the relationship diagram and make the same
type of adjustments as you did with the diagram for the one-
to-one relationship. Your revised diagram should look like the one in
Figure 10.37. (Note that the middle line of the crow’s foot symbol is the
significant connection point—it should point directly to the foreign key.)
Resolving Multivalued Fields—Revisited
Back in Chapter 7 you learned how to resolve a multivalued field by us-
ing this generic procedure:
1. Remove the field from the table and use it as the basis for a new
table. If necessary, rename the field in accordance with the field
naming guidelines that you learned earlier in this chapter.
Figure 10.36. The existing one-to-many relationship between the BUILDINGS and ROOMS tables.
Buildings Rooms
PKPKBuilding Number
Number of Floors
Elevator Access
Site Parking Available
Room Number
Square Footage
Type of Room
Phone Available
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Establishing Each Relationship 359
2. Use a field (or set of fields) from the original table to relate the orig-
inal table to the new table; try to select fields that represent the
subject of the table as closely as possible. The field(s) you choose
will appear in both tables.
3. Assign an appropriate name, type, and description to the new table
and add it to the final table list.
You used this procedure to resolve a multivalued field called CATEGORIES
TAUGHT in an INSTRUCTORS table. Figure 10.38 shows the original ver-
sion of the table and the results of applying the procedure.
There’s one final fact about a multivalued field that you need to learn:
An inherent one-to-many relationship exists between a given set of val-
ues within a multivalued field and the record in which they reside.
You’ll see this when you examine the original INSTRUCTORS table in
Figure 10.38. A single instructor (such as Kendra Bonnicksen) can
teach one or more categories (DTP, SS, WP)—this holds true for every
record in the table.
When you properly resolve the multivalued field, the tables produced by
the procedure inherit the relationship. This is clearly the case with the
revised INSTRUCTORS and new INSTRUCTOR CATEGORIES tables.
You can now establish this one-to-many relationship as you would any
Figure 10.37. Establishing the one-to-many relationship between the BUILDINGS and ROOMS tables.
Buildings Rooms
PKBuilding Number
Number of Floors
Elevator Access
Site Parking Available
PKRoom Number
Square Footage
Type of Room
Phone Available
Building Number FK
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360 Chapter 10 Table Relationships
other. (Of course, this assumes that you’ve assigned a primary key to
the INSTRUCTORS table.) Figure 10.39 shows the results of properly
establishing this relationship.
The INSTRUCTOR ID field in the INSTRUCTOR CATEGORIES table serves
as a foreign key and helps to establish the one-to-many relationship
between the INSTRUCTORS and INSTRUCTOR CATEGORIES tables.
Figure 10.38. The original resolution of the CATEGORIES TAUGHT multivalued field.
Instructors
InstStreet Address 3131 Mockingbird Lane 7402 Kingman Drive 4141 Lake City Way 970 Phoenix Avenue
InstCity Seattle Redmond Seattle Bellevue
InstFirst Name
Shannon Estela
Timothy Kendra
InstLast Name
McLain Pundt
Ennis Bonnicksen
<< other fields >>
......
......
......
......
Category Taught
Instructor Categories
InstFirst Name Kendra
InstLast Name Bonnicksen
Timothy
Kendra
Ennis
Bonnicksen Kendra Bonnicksen Timothy Ennis
Timothy Ennis Shannon McLain
DTP SS WP WP DB OS DB
Shannon McLain SS
Instructors
InstStreet Address 3131 Mockingbird Lane 7402 Kingman Drive 4141 Lake City Way 970 Phoenix Avenue
InstCity Seattle Redmond Seattle Bellevue
InstFirst Name
Shannon Estela
Timothy Kendra
InstLast Name
McLain Pundt
Ennis Bonnicksen
<< other fields >>
......
......
......
......
Categories Taught DTP, SS, WP
DB, SS DTP, WP, PG
WP, DB, OS
Figure 10.39. Establishing the one-to-many relationship between the INSTRUCTORS and INSTRUCTOR CATEGORIES tables.
Instructors Instructor Categories
Category Taught DTP SS WP WP DB OS DB SS
Instructor ID 60001 60001 60001 60002
Instructor ID 60001 60002 60003 60004
InstStreet Address 3131 Mockingbird Lane 7402 Kingman Drive 4141 Lake City Way 970 Phoenix Avenue
InstCity Seattle Redmond Seattle Bellevue
InstFirst Name
Shannon Estela
Timothy Kendra
InstLast Name
McLain Pundt
Ennis Bonnicksen
<< other fields >>
......
......
......
...... 60002 60002 60003 60003
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Establishing Each Relationship 361
INSTRUCTOR ID is also part of the composite primary key for the INSTRUC-
TOR CATEGORIES table; a given combination of INSTRUCTOR ID and CATE-
GORY TAUGHT values uniquely identifies a specific record in the table.
The Many-to-Many Relationship
You establish a many-to-many relationship with a linking table. This is
a new table that you’ll create using the following three-step procedure.
1. Define the linking table by taking copies of the primary key from
each table in the relationship and using those keys to form the struc-
ture of the table. These fields will serve two distinct purposes within
the linking table: Together they constitute the table’s composite pri-
mary key, and each is a unique foreign key that helps to establish a
relationship between its parent table and the linking table.
2. Give the linking table a name that represents the nature of the
relationship between the two tables. For example, if you’re estab-
lishing a many-to-many relationship between a PILOTS table and a
CERTIFICATIONS table, you might choose to call the linking table
PILOT CERTIFICATIONS.
3. Add the linking table to the final table list and make the proper en-
tries for “Table Type” and “Table Description.”
Figure 10.40 shows how you establish the many-to-many relationship
between the STUDENTS and CLASSES tables. (Note the new diagram
symbol used to represent a linking table.)
❖ Note You could have used STUDENT SCHEDULES or CLASS SCHEDULES as the name of the linking table; STUDENT
CLASSES just happens to be my personal preference. The point to
remember is that you should use a name that makes the most
sense to you or to the organization.
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362 Chapter 10 Table Relationships
Creating a linking table produces a few noteworthy results.
• The original many-to-many relationship has been dissolved be-
cause there is no longer a direct relationship between the STU-
DENTS and CLASSES tables. The original relationship has been
replaced by two one-to-many relationships: one between STU-
DENTS and STUDENT CLASSES and another between CLASSES
and STUDENT CLASSES. In the first relationship, a single record
in STUDENTS can be associated with one or more records in STU-
DENT CLASSES, but a single record in STUDENT CLASSES table
can be associated with only one record in STUDENTS. In the sec-
ond relationship, a single record in the CLASSES table can be as-
sociated with one or more records in STUDENT CLASSES, but a
single record in STUDENT CLASSES can be associated with only
one record in CLASSES.
• The STUDENT CLASSES linking table contains two foreign keys.
STUDENT ID and CLASS ID are both copies of the primary keys from
the STUDENTS and CLASSES tables respectively; therefore, each
Figure 10.40. Establishing the many-to-many relationship between the STUDENTS and CLASSES tables.
Student Classes
Classes
Class ID
Instructor ID
Class Name
Class Description
Category
PK
Student ID CPK/FK
Class ID CPK/FK
Students
Student ID StudFirst Name StudLast Name StudStreet Address StudCity StudState StudZipcode StudHome Phone StudEmail Address Social Security Number
PK
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Establishing Each Relationship 363
is a foreign key by definition. As such, they help to establish the
relationship between their parent tables and the linking table.
• The STUDENT CLASSES linking table has a composite primary key
composed of the STUDENT ID and CLASS ID fields. Except in rare in-
stances, a linking table always contains a composite primary key.
(This rule applies to the database’s logical design only. There are
various reasons why you might break this rule when you trans-
form the logical design into a physical design, but this is a discus-
sion that is beyond the scope of this book.) It’s important to note
that you’ll occasionally have to add more fields to the linking table
in order to guarantee a unique primary key value. For example,
assume the school decides to record student schedules for every
term of the school year (fall, winter, and spring). You would have
to add a new field, perhaps called TERM, and designate it as part of
the composite primary key. This would enable you to enter an-
other instance of a given student and class into the table, but for
a different term; a student may need to retake a class during the
spring term because he failed the class in the fall term.
• The linking table helps to keep redundant data to an absolute mini-
mum. There is no superfluous data in this table at all. In fact, the
main advantage of this table structure is that it allows you to en-
ter as few or as many classes for a single student as is necessary.
Later in the database-design process, you’ll learn how to create
views to draw the data from these tables together in order to
present it as meaningful information.
• The name of the linking table reflects the purpose of the relation-
ship it helps establish. The data stored in the STUDENT CLASSES
table represents a student and the classes in which he or she is
enrolled.
As you work with many-to-many relationships, there will be instances in
which you will need to add fields to the linking table in order to reduce
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data redundancy and further refine structures of the tables participating
in the relationship. For example, assume you’re working on a new data-
base with a colleague and he’s just brought the ORDERS and PROD-
UCTS tables in Figure 10.41 to your attention.
You note that there’s a many-to-many relationship between the tables
and then realize that your colleague tried to establish this relationship
by taking a copy of the PRODUCT NUMBER and QUOTE PRICE fields from the
PRODUCTS table and incorporating them into the ORDERS table. He
thought that this was the best way to associate various products with a
particular order. The presence of these fields in the ORDERS table, how-
ever, produces a large amount of redundant data. Figure 10.42 illus-
trates this problem quite clearly.
You can enter only one product number, quantity ordered, and quote
price for any given record; therefore, you’ll have to enter a new record
into the table for each item a customer places on his order. Customer
number 9001, for example, included eight items on an order he made
on May 16, so there are eight records in the table for this order alone.
Based on what you’ve learned earlier in this chapter, you know that
this is an improper way to establish this relationship. You also know
Figure 10.41. Is there a problem with either of these tables?
Orders
PK Product Number
ProdDescription
ProdName
Category
Quote Price
Wholesale Price
Customer Number
Order Date
Ship Date
Employee ID
Quote Price
Product Number
Quantity Ordered
Order Number
Products
PK
FK
FK
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Establishing Each Relationship 365
that you can establish the relationship properly by creating and using
a linking table. So you remove the PRODUCT NUMBER field from the OR-
DERS table, establish the relationship in the appropriate manner, and
revise the relationship diagram. Figure 10.43 shows the results of
your work.
Figure 10.42. Redundant data caused by an improperly established many-to- many relationship.
Orders
Order Number
1000
1000
1000
1000
1000
1000
1000
1000
1001
1001
1001
Customer Number
9001
9001
9001
9001
9001
9001
9001
9001
9012
9012
9012
Order Date
05/16/02
05/16/02
05/16/02
05/16/02
05/16/02
05/16/02
05/16/02
05/16/02
05/16/02
05/16/02
05/16/02
Quote Price
8.95
3.75
6.50
5.99
4.45
6.50
31.50
5.00
6.50
4.00
6.35
Product Number
410001
410004
410007
410005
410015
410011
410021
410029
410011
410015
410022
Quantity Ordered
4
12
5
6
11
5
2
8
5
3
12
<< other fields >>
......
......
......
......
......
......
......
......
......
......
......
Figure 10.43. Properly establishing the many-to-many relationship between the ORDERS and PRODUCTS tables.
Order Details
Order Number CPK/FK
Product NumberCPK/FK
Product Number
ProdDescription
ProdName
Category
Quote Price
Wholesale Price
Products
PK
Orders
PK
Customer Number
Order Date
Ship Date
Employee ID
Quote Price
Product Number
Quantity Ordered
Order Number
FK
FK
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You’ve eliminated the redundant data in the ORDERS table, but you
still have two minor problems.
1. The QUOTE PRICE and QUANTITY ORDERED fields are no longer appropri-
ate for the ORDERS table; the ORDERS table’s primary key does
not exclusively identify their values, and they bear no relationship
to any of the remaining fields in the table. They do, however, relate
to a particular PRODUCT NUMBER that’s part of a given order within
the ORDER DETAILS table.
2. You have duplicate data because there are two copies of the QUOTE
PRICE field: one in the ORDERS table and another in the PROD-
UCTS table.
So you resolve the first problem by removing the QUOTE PRICE and QUAN-
TITY ORDERED fields from the ORDERS table and incorporating them
within the ORDER DETAILS table. You then resolve the second problem
by deleting the QUOTE PRICE field from the PRODUCTS table; it makes
more sense to associate a quote price with a product as it’s being or-
dered. Finally, you modify the relationship diagram to reflect the
changes you made to the structures. Figure 10.44 shows your revised
diagram.
Figure 10.44. The revised ORDER DETAILS linking table.
Order Details
Order Number CPK/FK
Product NumberCPK/FK
Orders
PK Product Number
ProdDescription
ProdName
Category
Wholesale Price
Customer Number
Order Date
Ship Date
Employee ID
Order Number
Products
PK
FK
FK
Quantity Ordered
Quote Price
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Establishing Each Relationship 367
When you establish a many-to-many relationship between a pair of ta-
bles, make certain you check each table and determine whether there
are any fields that you should transfer to the linking table. When in
doubt, load all the tables with sample data; this will usually reveal any
potential problems.
Self-Referencing Relationships
Establishing a self-referencing relationship will be a relatively simple
task now that you know how to establish a relationship between a pair
of tables.
One-to-One and One-to-Many
You use a primary key and a foreign key to establish these self-referenc-
ing relationships, just as you do with their dual-table counterparts. The
difference here, however, is that the foreign key will reside in the same
table as the primary key to which it refers. You’ll often find that the for-
eign key is already part of the table’s structure. If the foreign key does
not already exist, you’ll simply create one.
Let’s revisit the MEMBERS table example from Figure 10.20. Recall that
this table has a self-referencing one-to-one relationship because a given
member can sponsor only one other member within the organization;
❖ Note You won’t encounter this problem very often if you faith- fully follow the design process you’ve learned thus far. It will typi-
cally arise, however, when you’re trying to incorporate a pair of
tables from an existing or legacy database and you haven’t taken
the time to refine their structures properly. You’ll also encounter
this problem when you work with someone who has little or no
database-design experience.
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368 Chapter 10 Table Relationships
the SPONSOR ID field stores the member identification number of the
member acting as a sponsor. Because the SPONSOR ID field draws its val-
ues exclusively from the MEMBER ID field, it acts as the foreign key for
the relationship. You establish the relationship by officially designating
the SPONSOR ID field as the foreign key and notating it as such in the re-
lationship diagram. Figure 10.45 shows the revised relationship dia-
gram for the MEMBERS table.
Now, consider the STAFF table example in Figure 10.46. You may re-
member that this table has a self-referencing one-to-many relationship
because a single staff member can manage one or more other staff
members.
There is currently no means of associating a given staff member to other
staff members within the table; therefore, you must create a new field
that will act as the foreign key and enable you to establish the relation-
ship. Let’s assume you create a new foreign key field called MANAGER ID
Figure 10.45. Establishing the self-referencing one-to-one relationship for the MEMBERS table.
Members
PKMember ID
MbrFirst Name
MbrLast Name
MbrStreet Address
MbrCity
MbrState
MbrZipcode
MbrPhone Number
Status
Date Enrolled
FKSponsor ID
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Establishing Each Relationship 369
that will draw its values exclusively from the STAFF ID field. You now es-
tablish the relationship by officially designating MANAGER ID as the foreign
key and notating it as such in the relationship diagram. Figure 10.47
shows the revised relationship diagram for the STAFF table.
You probably noticed that the “one” side of the relationship line points
to the MANAGER ID field and the “many” side of the line points to the
STAFF ID field. This is perfectly acceptable because a manager will man-
age one or more staff members, but a given staff member reports to
only one manager. (As you may have intuitively guessed, the “one” side
of the line commonly points to the primary key and the “many” side to
the foreign key.)
As you work with self-referencing one-to-one and one-to-many relation-
ships, take a moment and examine each table’s structure carefully.
You’ll occasionally find that you can (or may need to) modify and im-
prove the existing structure in order to eliminate the relationship. I
know what you’re wondering: “But why would I want to do that?”
Figure 10.46. The current structure of the STAFF table.
Staff
PKStaff ID
StaffFirst Name
StaffLast Name
StaffStreet Address
StaffCity
StaffState
StaffZipcode
StaffPhone Number
Position
Date Hired
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Retrieving information from tables with these types of relationships can
be tedious and somewhat difficult. (A discussion of the reasons for this
is, unfortunately, outside the scope of this work.) Additionally, the very
presence of the relationship can indicate the need for new field and ta-
ble structures.
Consider the STAFF table once again. Does it occur to you that if there
is a need to track staff members who are managers, there could be a
need to track the departments they manage? If this is true, then there
must be other facets of the departments that you need to track in the
database. You should now conduct a quick interview with the appropri-
ate staff members to answer these questions and then take the appro-
priate action based on their responses.
Let’s assume you were right and the organization does want to track de-
partmental data. Figure 10.48 shows one possible approach you might
use to accomplish this task.
Figure 10.47. The revised STAFF table with the new MANAGER ID foreign key.
Staff
PKStaff ID
StaffFirst Name
StaffLast Name
StaffStreet Address
StaffCity
StaffState
StaffZipcode
StaffPhone Number
Position
Date Hired
Manager ID FK
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Establishing Each Relationship 371
These new structures and relationships enable you to track the data ef-
ficiently and will provide a wide variety of information about the depart-
ments. (You will, of course, ensure that the new fields and tables
conform to the various design elements that you’ve learned thus far.)
It’s important to note that self-referencing relationships do have their
place within a well-designed database. You should be vigilant, however,
and make certain that each self-referencing relationship does indeed
serve a useful purpose.
The Many-to-Many Relationship
You use a linking table to establish this type of self-referencing relation-
ship, just as you do with its dual-table counterpart. Establishing this
relationship is slightly different in that the fields you use to build the
linking table come from the same parent table.
Staff
PKStaff ID
StaffFirst Name
StaffLast Name
StaffStreet Address
StaffCity
StaffState
StaffZipcode
StaffPhone Number
Date Hired
Department ID
DeptCategory
Maximum Staff Level
DeptNameDepartment Staff
Department ID CPK/FK
Position
Section
Staff ID CPK/FK
Department
PK
Figure 10.48. Results of eliminating the self-referencing relationship and adding new structures to track departmental data.
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372 Chapter 10 Table Relationships
Let’s revisit the PARTS table example from Figure 10.24. Recall that this
table has a self-referencing many-to-many relationship because a par-
ticular part can comprise several different component parts, and that
part itself can be a component of other parts. You establish this rela-
tionship as you would any other many-to-many relationship—with a
linking table. There is currently no way to associate a given part to other
parts within the table, so you must create a new field for this purpose.
Say, for example, that you create a field called COMPONENT ID. This field
will store the part identification number of a part that serves as a com-
ponent of a parent part. You can now use the PART ID and COMPONENT ID
fields as the basis for the linking table. For the sake of our example,
we’ll assume that the name of the new linking table is PART COMPO-
NENTS. Once you’ve created and named the linking table, be sure to re-
vise the relationship diagram for the PARTS table. Figure 10.49 shows
the results of your work.
As you can see, the PARTS table now has two distinct one-to-many rela-
tionships with the PART COMPONENTS table. The first relationship is
established via the PART ID field and the second relationship is estab-
lished via the COMPONENT ID field. Figure 10.50 illustrates how these re-
Parts
PK Part Components
CPK/FK
CPK/FK
Part ID
Part Description
Part Name
Category
Retail Price
Wholesale Price
Part ID
Component ID
Figure 10.49. Establishing the self-referencing many-to-many relationship for the PARTS table.
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Establishing Each Relationship 373
lationships work. Note that a clamp assembly (Part ID 704) contains
three components and is itself a component of a seat assembly (Part ID
707) and a frame assembly (Part ID 711).
Now, use the techniques you’ve just learned to establish all of the rela-
tionships you’ve identified among the tables in the database. Make ab-
solutely certain you create a diagram for each relationship—you’re
going to add new information to these diagrams as the design process
further unfolds.
Reviewing the Structure of Each Table
Review all of the table structures after you’ve established the relation-
ships between tables. Remember that you made modifications to the ex-
isting table structures and created several new table structures as you
established the relationships; therefore, you want to make certain that
each table conforms to the Elements of the Ideal Table.
Part NamePart ID
Parts
<< other fields >>
Clamp Assembly
701
......
Top Clamp
702
......
Bottom Clamp
703
......
Fastening Bolt
704
......
Seat Assembly
705
......
Saddle
706
......
Seatpost
707
......
Frame Assembly
708
......
Body Tube
709
......
Front Fork Tube
710
......
Rear Stay Tube
711
......
Part Components
Part ID
704
704
707
707
Component ID
702
703
704
705
707 706
711 708
711 709
704 701
711 710
711 704
Figure 10.50. Data relationships between the PARTS and PART COMPONENTS tables.
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374 Chapter 10 Table Relationships
Elements of the Ideal Table
• It represents a single subject, which can be an object or event.
• It has a primary key.
• It does not contain multipart or multivalued fields.
• It does not contain calculated fields.
• It does not contain unnecessary duplicate fields.
• It contains only an absolute minimum amount of redundant data.
When you determine that a table does not comply with the Elements of
the Ideal Table, identify the problem and make the necessary modifica-
tions. Then, take the table through the appropriate stages of the data-
base-design process until you return to this point. You shouldn’t
encounter any problems with the tables if you’ve been following proper
procedures thus far.
Refining All Foreign Keys
You now know that a primary key becomes a foreign key when you use
it to establish a relationship between a pair of tables in a one-to-one or
one-to-many relationship. As with any other key that you’ve worked
with so far, a foreign key must comply with a specific set of elements.
These elements are collectively known as the Elements of a Foreign Key.
Elements of a Foreign Key
• It has the same name as the primary key from which it was copied.
You should adhere to this rule unless there is an absolutely com-
pelling reason not to do so. (Review the discussion of the Alias
field specification element in Chapter 9. It provides an example of
an occasion when you might decide to break this rule.) Consider
the relationship diagram in Figure 10.51, and note that the for-
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Refining All Foreign Keys 375
eign keys have different names than the primary keys to which
they refer.
The fact that the names are different poses a problem because
you can’t be sure that the foreign keys are truly valid and actually
refer to the primary keys. Is EMP # truly equivalent to EMPLOYEE
NUMBER? Is “Emp” really a shortened version of “Employee,” or
does it mean something else? Why did someone choose to use CLI-
ENT # in the ORDERS table instead of CUSTOMER ID? Is there any
difference between the two? Do they store the same type of data?
These are questions you must answer before you can do anything
else with these tables and their respective relationships.
You could make a relatively reasonable argument that the names
are close enough to assume that the foreign keys are indeed valid.
If there’s any doubt, you could test your assumption by loading
the tables with sample data. You really shouldn’t have to take the
time to do this, however. Imagine having to do this for 15 or 20 re-
lationships; the amount of wasted time adds up.
PK
PK
Employee
Employee Number
EmpFirst Name
EmpLast Name
EmpStreet Address
EmpCity
EmpState
EmpZipcode
EmpPhone Number
Position
Hourly Rate
Date Hired
Orders
Client # FK
Order Date
Ship Date
Emp # FK
Order Number PK
Customers
Customer ID
CustFirst Name
CustLast Name
CustStreet Address
CustState
CustZipcode
CustPhone
CustEmail Address
Figure 10.51. Primary keys and foreign keys with mismatched names.
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376 Chapter 10 Table Relationships
You won’t have to ask these questions or perform these tests at all
when you adhere to this element. Figure 10.52 shows a revised
version of the diagram that uses the proper foreign key names. In
this case, there is no ambiguity and little doubt that the foreign
keys are appropriate. You can examine this diagram nine months
from now and, with a quick glance, confidently ascertain the type
of relationships between the tables and how they’re established.
❖ Note I encounter this issue quite often when I’m asked to ana- lyze certain types of database problems. In many cases, the for-
eign keys are either completely inappropriate or manifest serious
data-integrity and relationship-integrity problems. Once I identify
the appropriate foreign keys (or revise the existing ones) and en-
sure that they comply with this particular element, a number of
problems disappear.
PK
PK
Employee
Employee Number
EmpFirst Name
EmpLast Name
EmpStreet Address
EmpCity
EmpState
EmpZipcode
EmpPhone Number
Position
Hourly Rate
Date Hired
Orders
Customer ID FK
Order Date
Ship Date
Employee Number FK
Order Number PK
Customers
Customer ID
CustFirst Name
CustLast Name
CustStreet Address
CustState
CustZipcode
CustPhone
CustEmail Address
CustCity
Figure 10.52. Foreign keys that comply with the first element of a foreign key.
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Refining All Foreign Keys 377
• It uses a replica of the field specifications for the primary key from
which it was copied. This supports the sixth element of an ideal
field, which you learned in Chapter 7 (“It retains a majority of its
properties when it appears in more than one table”). A foreign
key, however, has a few settings in both the General Elements
and Logical Elements categories that are slightly different from
those of its parent primary key.
There are four elements in the General Elements category that
you will modify when you define a field specification for a foreign
key.
a. Specification Type. Because a foreign key is based on an exist-
ing primary key, it inherits a replica of the primary key’s field
specifications; therefore, you designate the foreign key’s specifi-
cation type as “Replica.” This designation helps you ensure that
your foreign key specifications are consistent, and reminds you
to keep this specification synchronized with the primary key’s
specification.
b. Parent Table. The name of the foreign key’s parent table goes
here.
c. Source Specification. This is where you indicate the name of
the parent primary key. (Make certain you include the name of
the primary key’s parent table as well; this will make it easier
The only time I can justify and approve of using a different name
for the foreign key field is when I establish a self-referencing
relationship for a given table. This is reasonable because the
primary key and foreign key both reside within the table (in most
cases), and each must have a unique name.
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378 Chapter 10 Table Relationships
for you to find the primary key’s specification should you want
to compare it to the foreign key’s specification.)
d. Description. Compose a description that indicates the foreign
key’s purpose within the table.Figure 10.53 shows an example
of these modifications for an EMPLOYEE ID NUMBER field serving
as a foreign key in an ORDERS table.
You’ll also adjust five elements in the Logical Elements category
for the foreign key field specification.
a. Key Type. Set this element to “Foreign.” This is a rather obvi-
ous change, but one that you can accidentally overlook if
you’re not careful.
b. Uniqueness. You designate this element as “Non-unique”
because you want to be able to associate a single foreign key
value with any number of records in the parent table. In terms
of our example, you want to be able to associate a specific
Employee #
Employee ID Number
General Elements
Field Name:
Label:
Parent Table:
Shared By:
Alias(es):
Description:
Source Specification:
Specification Type: GenericUnique Replica
The identification number of an employee within our organization. The values in this field enable us to identify and keep track of the employees who place orders for our customers.
Employee ID Number from the EMPLOYEES table.
Orders
x
Figure 10.53. General Elements for the EMPLOYEE ID NUMBER foreign key field in the ORDERS table.
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Refining All Foreign Keys 379
employee with any number of orders. If you set this to
“Unique” instead, you could associate a given employee with
one order only, which would greatly limit his or her sales
potential! (In the case of a one-to-one relationship, however,
you’ll designate this element as “Unique” because you want to
associate a single foreign key value in the child table with only
one record in the parent table.)
c. Values Entered By. Unlike the parent primary key, you (or a
user) will enter values into the foreign key; therefore, you set
this element to “User.”
d. Range of Values. You must set this element in such a way that
you (or a user) can enter only existing values from the parent
primary key. (You’ll learn more about this and see a good
example in just a moment.)
e. Edit Rule. You normally set this to “Enter Now, Edits Allowed,”
although there might be instances (such as when the foreign
key comes from a validation table) when you can set this to
“Enter Later, Edits Allowed.” Allowing edits of foreign key val-
ues enables you to fix mistakes. For example, you might have
mistakenly entered employee ID number “100” for a given
order when you meant to enter “110.”
Figure 10.54 shows an example of these modifications for the
EMPLOYEE ID NUMBER foreign key field. (Note the setting for the
Range of Values—this is one good way to set this element.)
In order for you to see the significance of these modifications,
Figure 10.55 shows the Logical Elements category from the
Source Specification. (Recall that this element is in the General
Elements category; see Figure 10.53.)
• It draws its values from the primary key to which it refers. By defi-
nition, a foreign key’s range of values is limited to existing values
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380 Chapter 10 Table Relationships
of the primary key to which it refers. For example, you cannot
enter an invalid EMPLOYEE ID NUMBER into the ORDERS table. Any
EMPLOYEE ID NUMBER you enter into the ORDERS table must first
exist as an EMPLOYEE ID NUMBER in the EMPLOYEES table. This
ensures consistency among the values of both fields in both
tables and helps to establish relationship-level integrity.
Review the foreign keys in each table to make certain that they conform
to the Elements of a Foreign Key, and make the appropriate modifica-
tions to those that fail to do so. You really shouldn’t encounter any
problems if you’ve been faithfully following the design process up to this
point.
Logical Elements
Key Structure:
Non
Not Determined At This Time
Edit Rule:
Null Support: Nulls Allowed
Enter Now, Edits Not Allowed
Enter Later, Edits Allowed
Primary
AlternateForeign
No Nulls
Uniqueness: Unique
Required Value: No Yes
Comparisons Allowed:
x
x
x
x
Range of Values:
Default Value:
Values Entered By:
Operations Allowed:
Systemx
Key Type:
CompositeSimplex
Enter Later, Edits Not Allowed
<> <=>=
Other Fields
Same Fieldx =x
Value Expressionx <> <=>==
<> <=>==x
All
All
All
Same Field
Other Fields Concatenation
All
All
+
+
x
x
Value Expression All Concatenation+ x
Concatenation
≠ ≠ ≠
÷ ÷ ÷
Any existing Employee ID Number in the EMPLOYEES table.
Enter Now, Edits Allowedx
Non-unique
User
–
–
–
Figure 10.54. Logical Elements for the EMPLOYEE ID NUMBER foreign key field in the ORDERS table.
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Establishing Relationship Characteristics 381
Establishing Relationship Characteristics
Now you’ll establish the characteristics of each relationship. These
characteristics indicate what will occur when you delete a record, the
type of participation each table bears within the relationship, and to
what degree each table participates in the relationship.
Defining a Deletion Rule for Each Relationship
The first characteristic you’ll establish for the relationship is a deletion
rule. This rule determines what your RDBMS should do when you place
Logical Elements
Key Structure:
Non
Not Determined At This Time
Edit Rule:
Null Support: Nulls Allowed
Enter Now, Edits Allowed
Enter Now, Edits Not Allowed
Enter Later, Edits Allowed
Primary
AlternateForeign
No Nulls
Uniqueness: Non-unique Unique
Required Value: No Yes
Comparisons Allowed:
x
x
x
x
x
Range of Values:
Default Value:
Values Entered By: User
Operations Allowed:
Systemx
Key Type:
CompositeSimplex
Enter Later, Edits Not Allowed
<> <=>=
Other Fields
Same Fieldx =x
Value Expressionx <> <=>==
<> <=>==x
All
All
All
Same Field
Other Fields Concatenation
All
All
+
+
x
x
Value Expression All Concatenation+ x
Concatenation
1000–9999
≠ ≠ ≠
÷ ÷ ÷
–
–
–
Figure 10.55. Logical Elements for the EMPLOYEE ID NUMBER primary key field in the EMPLOYEES table.
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382 Chapter 10 Table Relationships
a request to delete a given record in the parent table of the relationship.
Deletion rules are crucial to relationship-level integrity because they
help guard against orphaned records, which are records in the child
table that have no relationship whatsoever to any records in the parent
table.
These are the five types of deletion rules you can define and the actions
the RDBMS should take when a given rule is in force:
1. Deny. The RDBMS will not delete the record in the parent table,
but will instead keep the record and designate it as “inactive.”
2. Restrict. The RDBMS will not delete the record in the parent table if
related records exist in the child table. You must have the RDBMS
delete all of the related records in the child table before you can
have it delete the record in the parent table.
3. Cascade. The RDBMS will take two specific actions: It will delete
the record in the parent table, and it will also automatically delete
all related records in the child table.
4. Nullify. The RDBMS will delete the record in the parent table and
will then update the foreign key values of related records in the
child table to null. If you are going to use this deletion rule, you
must modify the foreign key’s field specifications and set the Null
Support logical element to “Nulls Allowed.”
5. Set Default. The RDBMS will delete the record in the parent table
and will then update the foreign key values of related records in
the child table to the current Default Value logical element setting
in the foreign key’s field specifications. Obviously, you must have a
setting for the Default Value element in order to use this rule.
Use a Restrict deletion rule as a matter of course and the other rules as
appropriate. The best way to determine which deletion rule is appropri-
ate for a given relationship is to examine the relationship diagram. Con-
sider the diagram in Figure 10.56.
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Establishing Relationship Characteristics 383
Select a relationship, look at the diagram, and pose the following
question:
When a record in the (name of parent table) table is deleted, what
should happen to related records in the (name of child table)
table?
Here the question is framed in a generic manner so that you can under-
stand the premise behind it. When you pose this question for a pair of
tables in a particular relationship, substitute the phrases within the pa-
rentheses with the appropriate table names. If you’re working with the
Product Number
Products
PK
Order Details
Order Number CPK/FK
Product NumberCPK/FK
Orders
PK
Customer ID
Employee Number
Order Number
FK
FK
Customers
PKCustomer ID
Employees
PK
Manager ID
Employee Number
FK
Figure 10.56. What deletion rule is appropriate for a given relationship?
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relationship between the EMPLOYEES and ORDERS table, you could
pose the question in this manner:
When a record in the EMPLOYEES table is deleted, what should
happen to related records in the ORDERS table?
The answer you receive depends on how the organization is using the
data within the tables and will usually indicate which deletion rule you
should use for the relationship.
You can’t delete an employee record; you have to designate the
employee as inactive. (Use a Deny rule.)
You can’t delete an employee record if there are related order
records. (Use a Restrict rule.)
You must first delete the orders associated with the employee
from the ORDERS table and then delete the employee from the
EMPLOYEES table. (Use the Restrict rule.)
All orders associated with the employee must be deleted from
the ORDERS table as well. (Use the Cascade rule.)
The employee number for all orders associated with the
employee must be deleted. (Use a Nullify rule.)
The employee number for all orders associated with the
employee must be reset to the lead salesperson’s employee num-
ber. (Use a Set Default rule.)
If you (or the people you’re working with) cannot easily provide an an-
swer, make note of the relationship and continue with another rela-
tionship. You’ll revisit all of these relationships when you establish
business rules for the database later in Chapter 11. For now, let’s as-
sume you received the first reply and you’re going to use a Deny rule
for the relationship.
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Once you’ve identified the type of deletion rule you want to use for the
relationship, designate the rule on the relationship diagram. Use (D) for
Deny, (R) for Restrict, (C) for Cascade, (N) for Nullify, and (S) for Set De-
fault. Place the designation under the connection line of the parent ta-
ble. Figure 10.57 shows the revised relationship diagram for the
EMPLOYEES and ORDERS tables.
You always set the deletion rule from the perspective of the parent table
because it is the more important of the two tables within the relation-
ship. Deleting a record in the parent table will always have some effect
on related records in the child table, but deleting a record in the child
table will have no effect on the related record in the parent table. (There
is a specific circumstance in which you might want to establish a Re-
strict deletion rule for the child table, and you’ll learn about it in Chap-
ter 11.)
The question you use to determine the deletion rule for a self-referencing
relationship is just slightly different from the one you just used for a
dual-table relationship.
When a record in the (name of parent table) table is deleted, what
should happen to the foreign key values of the other records that
were related to it?
Orders
PK
Customer ID
Employee Number
Order Number
FK
FK
Employees
PK
Manager ID
Employee Number
FK (D)
Figure 10.57. Designating a Restrict deletion rule for the relationship between the EMPLOYEES and ORDERS tables.
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If you’re working with the self-referencing relationship for the EMPLOY-
EES table, you could pose the question in this manner:
When a record in the EMPLOYEES table is deleted, what should
happen to the foreign key values of the other records that were
related to it?
Once again, the reply will usually indicate which deletion rule you
should use for the relationship.
You can’t delete a record for an employee who’s currently man-
aging other employees. (Use a Restrict rule.)
If the employee you want to delete is a manager, you cannot
delete his record until you assign the employees he manages to a
different manager. (Use the Restrict rule.)
If the employee whose record you want to delete is a manager,
the MANAGER ID must be deleted from the record of every
employee he currently manages. (Use a Nullify rule.)
If the employee whose record you want to delete is a manager,
the MANAGER ID must be reset to the senior manager’s employee
number in the record of every employee he currently manages.
(Use a Set Default rule.)
Say that you received the fourth reply and have determined that you’re
going to use a Set Default deletion rule for the relationship. You now
❖ Note The Cascade rule is notably absent from this example be- cause it doesn’t apply to the relationship at all; you don’t want to
fire employees just because their manager is leaving the organiza-
tion. This rule is still a viable option in some instances, so do
keep it in mind when you’re establishing deletion rules for other
self-referencing relationships.
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Establishing Relationship Characteristics 387
complete the process by designating the rule on the relationship dia-
gram. Figure 10.58 shows the results of your work.
Identifying the Type of Participation for Each Table
When you establish a relationship between a pair of tables, each table
participates in a particular manner. The type of participation you assign
to a given table determines whether a record must exist in that table be-
fore you can enter records into the related table. There are two types of
participation:
1. Mandatory. There must be at least one record in this table before
you can enter any records into the related table.
2. Optional. There is no requirement for any records to exist in this
table before you can enter records into the related table.
You’ll commonly determine the type of participation for most tables later
when you’re defining business rules, although you can quite often es-
tablish the type of participation for tables in relationships where the
type of participation for each table is obvious, is a result of common
sense, or is in accordance with some particular set of standards. For ex-
ample, consider the one-to-many relationship between the EMPLOYEES
and CUSTOMERS tables in Figure 10.59. (These are slightly different
versions of the tables in Figure 10.56.)
Employees
PK
Manager ID
Employee Number
FK (S)
Figure 10.58. Designating a Set Default deletion rule for the EMPLOYEES table self-referencing relationship.
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Assume that each customer must be assigned to a particular employee.
This employee acts as the customer’s account representative and takes
care of all transactions and communications between the organization
and that customer. Although each customer must be associated with a
particular employee, a given employee does not have to be associated
with any customer at all. Many employees perform other functions
within the organization that do not require customer interaction.
This scenario neither implies nor defines any special circumstances,
but does indicate the manner in which the organization conducts this
part of its business. As such, you can infer the following:
• You should designate a Mandatory type of participation for the EM-
PLOYEES table. This ensures that there is at least one employee
for you to assign to a given customer.
• You should designate an optional type of participation for the CUS-
TOMERS table. This allows you to enter any person employed by
the organization.
Once you’ve determined the type of participation for each table within
the relationship, designate each table’s participation on the relation-
ship diagram. Use a vertical line to represent a Mandatory type of par-
ticipation and a circle to represent an optional type of participation.
Figure 10.60 shows the revised relationship diagram for the EMPLOY-
EES and CUSTOMERS tables and also demonstrates how you indicate
Customers
Customer ID
Employee Number FK
PK
Employees
PKEmployee Number
(D)
Figure 10.59. What type of participation should you assign to each table?
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Establishing Relationship Characteristics 389
each type of participation. Note that you place the symbol representing
the type of participation outside of the symbol that represents the type
of relationship.
The type of participation also applies to a self-referencing relationship,
although in a slightly different manner. Because of the nature of a self-
referencing relationship, you designate the type of participation for the
primary key and foreign key fields in the table. Figure 10.61 shows a re-
vised relationship diagram for the STAFF table you worked with earlier
in this chapter.
Customers
Customer ID
Employee Number FK
PK
Employees
PKEmployee Number
(D)
This line symbolizes a mandatory type of participation for this table.
This circle symbolizes an optional type of participation for this table.
Figure 10.60. Designating the type of participation for the EMPLOYEES and CUSTOMERS tables.
Staff
PK
Manager ID
Staff ID
FK
(S)
Figure 10.61. Designating the type of particpation for the primary and foreign keys of the STAFF table.
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390 Chapter 10 Table Relationships
In this case, you must have at least one staff member with a valid staff
identification number (the primary key) who can serve as a manager.
Conversely, you need not provide a manager identification number (the
foreign key) for a brand-new staff member; this person may have just
been hired earlier today and has not yet been assigned to a particular
department or project.
Identifying the Degree of Participation for Each Table
Now that you’ve determined how each table will participate within the
relationship, you must determine the degree to which each table will
participate. The degree of participation indicates the minimum number
of records that a given table must have associated with a single record
in the related table and the maximum number of records that the table
is allowed to have associated with a single record in the related table.
The factors you use to determine the degree of participation—obvious
circumstances, common sense, or conformance to some set of stan-
dards—are the same as those you used to determine the type of partici-
pation. You’ll commonly identify the degree of participation for some
tables now and revisit the remaining tables when you define business
rules for the database.
You use two numbers separated by a comma and enclosed within pa-
rentheses to represent the degree of participation for a given table. The
first number indicates the required minimum number of related records
and the second number indicates the allowable maximum number of re-
lated records. For example, a degree of participation such as (2,11) indi-
cates that the table must have at least 2 but no more than 11 of its
records related to a single record in the other table.
Consider the EMPLOYEES and CUSTOMERS tables once again. There
is a one-to-many relationship between these tables, which means that a
given customer can be associated with only one employee and a given
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Establishing Relationship Characteristics 391
employee can be associated with any number of customers. (Yes, I
know; this is the obvious part.) Assume, however, that your organiza-
tion has just instituted a new policy that focuses sharply on quality
customer service. In order to ensure that each account representative
can deliver the level of service the organization requires, the policy stip-
ulates that he cannot be assigned to more than 15 customers at the
same time. Based on this scenario, you can infer that the degree of par-
ticipation for the EMPLOYEES table is (1,1) and the degree of participa-
tion for the CUSTOMERS table is (0,15).
Once you’ve identified the degree of participation for a particular table,
add the information to the relationship diagram. Designate the degree
of participation over the connection line of the appropriate table.
Figure 10.62 shows the revised relationship diagram for the EMPLOY-
EES and CUSTOMERS tables.
The degree of participation also applies to a self-referencing relation-
ship, although you designate it for the primary key and foreign key fields
in the table, just as you did with the type of participation. Figure 10.63
shows an updated version of the relationship diagram for the STAFF ta-
ble that includes the degree of participation information.
Customers
Customer ID
Employee Number FK
PK
Employees
PKEmployee Number
(D)
This indicates the minimum and maximum number of
customers to which an employee can be related.
This indicates the minimum and maximum number of
employees to which a customer can be related.
(1,1)
(0,15)
Figure 10.62. Designating the degree of participation for the EMPLOYEES and CUSTOMERS tables.
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392 Chapter 10 Table Relationships
STAFF ID has a degree of participation of (0,12) because a manager can
manage up to 12 staff members; a new manager who hasn’t yet been as-
signed to a department or project will have no (or 0) staff members to
manage. The degree of participation for MANAGER ID is (1,1) because a
given staff member is managed by only one manager.
You can designate an unlimited degree of participation for any table in a
dual-table relationship or key field in a self-referencing relationship by
using an “N” in place of the second number. For example, the ORDERS
table in Figure 10.64 has an unlimited degree of participation. Although
a new customer may have not yet placed an order, you will allow him to
place as many orders as he wishes. Imagine the impact on your organi-
zation’s business if you limited each customer to 35 orders! Your orga-
nization would soon be out of business, unless it could continually and
consistently acquire new customers.
Staff
PK
Manager ID
Staff ID
FK
(S)
(1,1)
(0,12)
Figure 10.63. Designating the degree of participation for the primary and foreign keys of the STAFF table.
Customers
Customer ID
Employee Number FK
PK
Orders
PKOrder Number
(R)
(1,1)
(0,N) Employee Number FK
Figure 10.64. Designating an unlimited degree of participation for the ORDERS table.
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Establishing Relationship Characteristics 393
Your task now is to set the relationship characteristics for every rela-
tionship you’ve established thus far. As you complete work on a given
relationship, be sure to update the relationship diagram so that it re-
flects the results of your work.
Verifying Table Relationships with Users and Management
The very last order of business is to verify the relationships. You can
perform this task relatively easily by using the following checklist:
1. Make sure that you’ve properly identified each relationship.
2. Make certain that you’ve properly established each relationship.
3. Make certain that each foreign key complies with the Elements of a
Foreign Key.
4. Make sure that you’ve established an appropriate deletion rule for
each relationship.
5. Make certain that you’ve identified the proper type of participation
for each table within a dual-table relationship and for the appro-
priate key fields in a self-referencing relationship.
6. Make certain that you’ve identified the proper degree of participa-
tion for each table within a dual-table relationship and for the ap-
propriate key fields in a self-referencing relationship.
If all the relationships check out and everyone you’re working with
agrees to this assessment, you can be confident that the relationships
are sound and ready to be incorporated into views.
A Final Note
The degree to which you can easily implement these three relationship
characteristics depends greatly upon your RDBMS. Most RDBMSs do
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394 Chapter 10 Table Relationships
not fully or inherently support all of the characteristics, but they do pro-
vide some basic support for the deletion rule and type of participation.
In most cases, however, you can use SQL and programming code to im-
plement these characteristics for any relationship in your database.
Relationship-Level Integrity
A relationship attains relationship-level integrity after you’ve verified
that it is properly established and its characteristics are suitably set.
Relationship-level integrity warrants the following:
• The connection between the two tables (or key fields) in a relation-
ship is sound. You accomplished this by using primary and for-
eign key fields to establish a one-to-one or a one-to-many
relationship and a linking table to establish a many-to-many
relationship.
• You can insert new records into each table in a meaningful manner.
You ensured this by designating the appropriate type of participa-
tion for each table (or key field) within the relationship.
• You can delete an existing record without producing any adverse
effects. You guaranteed this by assigning an appropriate deletion
rule for the relationship.
• There is a meaningful limit to the number of records that can be
interrelated within the relationship. You implemented this by des-
ignating the appropriate degree of participation for each table (or
key field) within the relationship.
As you know, relationship-level integrity is the third component of over-
all data integrity. (The first is table-level integrity and the second is
field-level integrity.) You’ll establish the final component of overall data
integrity in the next chapter when you learn how to establish business
rules for the database.
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Case Study 395
It’s now time to identify the relationships that exist for the tables that
appear on the final table list for Mike’s Bikes. You’ve assigned your as-
sistant, Zachary, to this part of the design process, and he’s currently
working with these tables:
CUSTOMERS
EMPLOYEES
INVOICES
PRODUCTS
VENDORS
Zachary’s first order of business is to identify the relationships that cur-
rently exist between the tables. He decides to meet only with Mike be-
cause there are few tables in this database, and he figures that Mike
should be familiar enough with the tables to help him verify the rela-
tionships.
Before Zachary meets with Mike, he creates a table matrix and identifies
as many relationships as possible. Figure 10.65 shows his completed
matrix.
CASE STUDY
1:1
Customers
Employees
Invoices
Products
Vendors
Customers Employees Products Vendors
1:1 1:N
?
?
Invoices
1:N
1:N
1:N
Figure 10.65. Identifying the relationships among the tables in the Mike’s Bikes database.
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396 Chapter 10 Table Relationships
Zachary then studies the table matrix closely and uses the appropriate
formula to determine the true relationship between each pair of tables.
Here is what he’s discovered so far:
CUSTOMERS and INVOICES bear a one-to-many relationship.
(1:1 + 1:N = 1:N)
EMPLOYEES and INVOICES bear a one-to-many relationship.
(1:1 + 1:N = 1:N)
PRODUCTS and INVOICES bear a many-to-many relationship.
(1:N + 1:N = M:N)
Now he diagrams the relationships, places them in a folder, and heads
to Starbucks for his meeting with Mike.
At the meeting, Mike and Zachary work on verifying the relationships.
They both determine that the three relationships are indeed correct,
and then Zachary brings Mike’s attention to the PRODUCTS and VEN-
DORS tables. He’s not quite sure about the relationship between them,
so he discusses the matter with Mike.
ZACHARY: “I wanted to ask you about the relationship between the
PRODUCTS and VENDORS tables. Can a single product
be associated with one or more vendors?”
MIKE: “Yes, in a manner of speaking. What I mean is that a sin-
gle type of product—such as a bike lock—can be associ-
ated with one or more vendors. But I give each lock its
own product number and treat it as a distinct item, re-
gardless of the vendor who supplies it. Now, if the true
meaning of your question is whether a single record in the
PRODUCTS table can be associated with one or more
records in the VENDORS table, then the answer is no be-
From the Library of Stephen Benoit
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Case Study 397
cause each record in the PRODUCTS table contains a ref-
erence to only one vendor in the VENDORS table.”
ZACHARY: “I thought as much. In that case, there’s a one-to-many
relationship between the VENDORS and PRODUCTS ta-
bles. I automatically figured that a single vendor could be
associated with many products in the PRODUCTS table.”
Zachary now diagrams the one-to-many relationship between the VEN-
DORS and PRODUCTS tables and continues with the next step.
He establishes each one-to-many relationship by taking a copy of the
primary key from the parent table and incorporating it within the struc-
ture of the child table (where it serves as a foreign key) and then revises
the relationship diagram accordingly. Figure 10.66 shows one of his re-
vised diagrams.
Now Zachary establishes the many-to-many relationship between the
INVOICES and PRODUCTS tables by creating a new linking table called
INVOICE PRODUCTS. He bases the new table on the INVOICE NUMBER field
from the INVOICES table and the PRODUCT NUMBER field from the PROD-
UCTS table. Figure 10.67 shows the revised relationship diagram for
these tables.
Invoices
PK
Customer Number
Employee Number
Invoice Number
FK
FK
Employees
PKEmployee Number
Figure 10.66. The relationship diagram for the EMPLOYEES and INVOICES tables.
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Zachary reviews each table structure to ensure that it conforms to the
Elements of the Ideal Table. Fortunately, he doesn’t have to make any
modifications because all of the table structures are sound. He now re-
fines the foreign keys in each table by making certain that each one
complies with the Elements of a Foreign Key. Finally, Zachary modifies
the appropriate items in the General Elements and Logical Elements
sections of each foreign key’s Field Specifications sheet. Figure 10.68
shows the modifications he’s made for one of the foreign keys. (I’ve high-
lighted the changes so that you can recognize them more easily.)
Zachary’s next task is to establish the appropriate relationship charac-
teristics for each relationship. He begins by defining a deletion rule for
each relationship and then identifies both the type of participation and
the degree of participation for each table within the relationship. He
completes his task by designating these characteristics on the relation-
ship diagram. Figure 10.69 shows one of the completed diagrams.
Mike and Zachary review and verify all the relationships one last time.
They agree that everything is complete, so they celebrate with a couple
of Mocha Brèves.
Invoice Products
Invoice Number CPK/FK
Product NumberCPK/FK
Invoices
PK Product Number
ProdDescription
ProdName
Category
Wholesale Price
Customer Number
Invoice Date
Ship Date
Employee ID
Invoice Number
Products
PK
FK
FK
Quantity Ordered
Quote Price Retail Price
Figure 10.67. Establishing and diagramming the many-to-many relationship between the INVOICES and PRODUCTS tables.
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Case Study 399
Logical Elements
Key Structure:
Non
Not Determined At This Time
Edit Rule:
Null Support: Nulls Allowed
Enter Now, Edits Not Allowed
Enter Later, Edits Allowed
Primary
Alternate
No Nulls
Uniqueness: Unique
Required Value: No Yes
Comparisons Allowed:
x
x
x
x
Range of Values:
Default Value:
Values Entered By:
Operations Allowed:
Systemx
Key Type:
CompositeSimplex
Enter Later, Edits Not Allowed
<> <=>=
Other Fields
Same Fieldx =x
Value Expressionx <> <=>==
<> <=>==x
All
All
All
Same Field
Other Fields Concatenation
All
All
+
+
x
x
Value Expression All Concatenation+ x
Concatenation
≠ ≠ ≠
÷ ÷ ÷
Any existing Customer Number in the CUSTOMERS table.
Enter Now, Edits Allowedx
Non-unique
User
Customer Number
General Elements
Field Name:
Label:
Parent Table:
Shared By:
Alias(es):
Description:
Source Specification:
Specification Type: GenericUnique Replica
Customer Number from the CUSTOMERS table.
Invoices
x
The identification number of a given customer. The values in this field enable us to identify and keep track of the customers who place orders for the products we provide.
–
–
–
Foreign
Figure 10.68. The General Elements and Logical Elements sections of the Field Specifications sheet for the CUSTOMER ID foreign key field in the INVOICES table.
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Summary
We opened this chapter with a discussion of the three types of relation-
ships that can exist between a particular pair of tables—one-to-one, one-
to-many, and many-to-many. You now know that the one-to-many rela-
tionship is the most common type of dual-table relationship and that
the many-to-many relationship gives rise to problems that must be re-
solved. You then learned about a self-referencing relationship, which is a
type of relationship that occurs between the records within a given ta-
ble. It is similar to a dual-table relationship in that it can be one-to-one,
one-to-many, or many-to-many.
Next, we discussed how to identify the relationships that exist among
the tables in a database. First you learned how to construct and use a
table matrix, and then you learned how to use associative and contex-
tual questions to help you identify a given relationship. We then dis-
cussed three formulas you could use to determine the true relationship
that exists between the tables in a dual-table relationship or between
the records in a self-referencing relationship.
The chapter continued with a discussion of how relationships are es-
tablished. You learned that one-to-one and one-to-many relationships
Invoices
PK
Customer Number
Employee Number
Invoice Number
FK
FK
Employees
PKEmployee Number (R)
(1,1)
(0,N)
Figure 10.69. The completed relationship diagram for the EMPLOYEES and INVOICES tables.
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Summary 401
are established by using primary keys and foreign keys, and that
many-to-many relationships are established using linking tables. We
then briefly revisited multivalued fields, and you learned how to use a
proper one-to-many relationship to resolve a multivalued field more ef-
ficiently. Next, we discussed self-referencing relationships, and you
now know that you establish them in a very similar manner to dual-
table relationships. You then learned that you must review all of the
table structures and ensure that they still conform to the Elements of
the Ideal Table.
Foreign keys were the next topic of discussion, and you learned that
every foreign key must comply with the Elements of a Foreign Key. You
now know that it can be very important for a foreign key to share the
same name as its parent primary key, that you must modify certain el-
ements of a field specification for a field that serves as a foreign key,
and that a foreign key must draw its values from the parent primary
key.
We then discussed relationship characteristics. You learned how to de-
fine a deletion rule for a relationship and that there are four ways you
can define it. Next, you learned how to identify the type of participation
and degree of participation for each table within a dual-table relation-
ship and for each key field in a self-referencing relationship. As you now
know, you can designate the type of participation as Mandatory or Op-
tional. You also know that the degree of participation gauges the mini-
mum and maximum number of interrelated records that can exist
within a given relationship. Finally, you learned that you must verify
the relationships with users and management and that you can use a
checklist to accomplish this task.
The chapter closed with a look at relationship-level integrity. You learned
that a relationship attains this type of integrity after you’ve verified that
it is properly established and its characteristics are suitably set.
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Review Questions
1. State two major reasons why a relationship is important.
2. Name the three types of relationships.
3. Which relationship will pose the most problems?
4. State two problems you could possibly encounter with a many-to-
many relationship.
5. What is a self-referencing relationship?
6. How do you begin the process of identifying the relationships
among the tables in the database?
7. What are the two types of questions you can ask to help you iden-
tify existing relationships?
8. What shorthand symbol do you use to designate a one-to-many
relationship in the table matrix?
9. How do you determine what type of relationship officially exists
between each pair of tables in the matrix?
10. How do you establish a one-to-many relationship?
11. True or False: Retrieving information from tables with a self-
referencing relationship can be tedious and somewhat difficult.
12. How do you establish a self-referencing many-to-many
relationship?
13. How do you refine the foreign keys in the database?
14. What two element categories must you modify for a foreign key’s
field specification?
15. What is the function of a deletion rule?
16. What two types of participation can you designate for a table?
17. What does the degree of participation indicate?
18. When does a relationship attain relationship-level integrity?
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11 Business Rules
You are remembered for the rules you break. —GENERAL DOUGLAS MACARTHUR
Topics Covered in This Chapter
What Are Business Rules?
Categories of Business Rules
Defining and Establishing Business Rules
Validation Tables
Reviewing the Business Rule Specifications Sheets
Case Study
Summary
Review Questions
Throughout the database-design process, you’ve performed tasks that
helped to establish various levels of data integrity. You’ve established
table-level integrity, field-level integrity, and relationship-level integrity
thus far. In doing so, you’ve ensured that the table and field structures
are sound, that data entered into the fields will be consistent and basi-
cally valid, and that relationships are meaningful and properly estab-
lished. In this chapter you’ll learn how to establish the final component
of overall data integrity: business rules.
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404 Chapter 11 Business Rules
What Are Business Rules?
A business rule is a statement that imposes some form of constraint on
a specific aspect of the database, such as the elements within a field
specification for a particular field or the characteristics of a given rela-
tionship. You base a business rule on the way the organization per-
ceives and uses its data, which you determine from the manner in
which the organization functions or conducts its business.
An important aspect of any design process is making choices. In data-
base design, for example, you must choose which data to store in the
database; you would not necessarily want or need to store every last
piece of data the organization might possibly use. The data you finally
choose to store and how you decide to store it will be determined by the
way the organization uses its data. A hospital may wish to store times of
various events to the second, whereas a warehouse requires only the
date for any given event.
To guide these and other choices you’ll be required to make during the
database-design process (and later, when you implement the database
in an RDBMS), you need a formal statement of the organization’s busi-
ness rules. These rules will influence a wide variety of database issues,
such as the data you collect and store, the manner in which you define
and establish relationships, the types of information that the database
can provide, and the very security and confidentiality of the data itself.
It is next to impossible to create a generic set of business rules that
could apply to two or more organizations. Each organization has its own
data and information requirements, and each has its own unique way of
conducting its business; therefore, every organization needs its own
specific set of business rules.
The following statement is an example of a typical business rule:
A SHIP DATE cannot be prior to an ORDER DATE for any given order.
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What Are Business Rules? 405
This particular business rule imposes a constraint on the Range of Val-
ues element of the field specifications for a SHIP DATE field. It will help
ensure that the value of SHIP DATE is meaningful within the context of a
sales order. Without this constraint, you could enter any date into the
field (including one prior to the ORDER DATE), making the SHIP DATE field’s
value absolutely meaningless. The business rule is what makes the SHIP
DATE field’s value contextually meaningful.
Because business rules depend on the manner in which an organization
perceives and uses its data, it is quite possible that a particular rule can
be used by several organizations, but for completely different reasons.
For example, say that the music department at Bel Air High School is
known far and wide for the quality of musicianship it develops in its
student musicians. The students are able to attain this level of musi-
cianship because they’re encouraged to focus their musical studies and
restrict themselves to learning no more than two instruments. In an-
other part of town, the music department at Lake City High School (a
private school) also imbues its student musicians with a high quality of
musicianship by helping the students focus their musical studies. The
students at this school, however, are restricted to learning no more than
two instruments due to school policy; the school’s inventory of musical
instruments is very limited.
Coincidentally, both schools are in the process of designing their own
database. In each case, the school will use the database to support its
daily operations and administrative functions. It so happens that each
database contains the tables shown in Figure 11.1.
Both schools are at the same stage of the database-design process and
are currently establishing business rules. As it turns out, each school is
using the following business rule in their respective databases:
A student cannot have more than two instruments checked out
at the same time.
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This business rule applies to the degree of participation between the
STUDENTS table and STUDENT INSTRUMENTS table. In this instance,
a single record in the STUDENTS table cannot be associated with more
than two records in the STUDENT INSTRUMENTS table where the value
of CHECK-IN DATE for each record is null; a null value in the CHECK-IN DATE
field indicates that the instrument is still in the student’s possession.
The rule does apply to both schools, yet each school requires it for a dif-
ferent reason. Bel Air High School requires the rule because of the man-
ner in which its music program has been established, whereas Lake
City High School requires the constraint because of the physical limita-
tions of its instrument inventory. The fact that both schools developed
an identical rule is pure coincidence. This example illustrates both that
a business rule is, indeed, based on the way an organization functions
or conducts its business and why every organization must have its own
specific set of business rules.
The example also illustrates another issue: You cannot establish con-
straints imposed by certain business rules, such as this one, within the
logical design of the database. For instance, there is no clear way for
Figure 11.1. Tables from the Bel Air High School and Lake City High School databases.
Student Instruments
Student ID
Instrument ID
Check-Out Date
Check-In Date
(1,1) (1,1)
(0,2)
(R)(R)
Instruments
Instrument ID
Product Line
Category
InstDescription InstrName
Manufacturer ID
Model
Estimated Value Date Acquired
Students
Student ID StudFirst Name StudLast Name StudStreet Address StudCity StudState StudZipcode StudHome Phone StudEmail Address Social Security Number
CPK/FK
CPK/FK (0,N)
CPK/FK
FK PKPK
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What Are Business Rules? 407
you to indicate that the CHECK-IN DATE values must be tested in order to
determine whether a student can check out another instrument. You
must instead address and establish the constraint outside of the logical
design of the database. How do you determine whether you can properly
represent a given constraint within this process? You do so by identify-
ing the type of business rule you’re defining.
Types of Business Rules
There are two major types of business rules: database oriented and
application oriented. Both types of business rules impose some form
of constraint and help enforce and maintain overall data integrity, but
they differ with regard to where and how they are established.
Database oriented business rules impose constraints that you can es-
tablish within the logical design of the database. You implement a given
constraint by modifying various field specification elements, relation-
ship characteristics, or a combination of the two. The statement from
which you derive the constraint is a database oriented business rule if
you can meaningfully and clearly establish the constraint by either of
these means. For example, say you have a VENDORS table and define
the following business rule for the VENDSTATE field in that table:
We conduct business exclusively with vendors from the Pacific
Northwest.
This business rule limits the values that you can enter into the VEND-
STATE field to WA, OR, ID, and MT. You can establish the business rule’s
constraint in a meaningful manner by modifying the Range of Values el-
ement in the field specifications for the VENDSTATE field. Figure 11.2
shows the modification.
Application oriented business rules impose constraints that you cannot
establish within the logical design of the database. You must instead es-
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408 Chapter 11 Business Rules
tablish them within the physical design of the database or within the
design of a database application, where they will be more applicable and
meaningful. (I use the term database application here to refer to a pro-
gram written in some RDBMS software that allows people in the organi-
zation to use the database easily and to perform tasks related to their
daily work activities.)
Here is an example of a typical application oriented business rule:
A customer with a “Preferred” status receives a 15% discount on
all purchases.
This business rule determines the amount of discount applied to a cus-
tomer’s purchases, based on a particular status. You cannot establish
Logical Elements
Key Structure:
Non
Not Determined At This Time
Edit Rule:
Null Support: Nulls Allowed
Enter Now, Edits Not Allowed
Enter Later, Edits Allowed
Primary
AlternateForeign
No Nulls
Uniqueness: Unique
Required Value: No Yes
Comparisons Allowed:
x
x
x
x
Range of Values:
Default Value:
Values Entered By:
Operations Allowed:
Systemx
Key Type:
CompositeSimple
Enter Later, Edits Not Allowed
<> <=>=
Other Fields
Same Fieldx =x
Value Expression
<> <=>==
<> <=>==
All
All
All
Same Field
Other Fields Concatenation
All
All
+
+
x
x
Value Expression All Concatenation+ x
Concatenation
≠ ≠ ≠
÷ ÷ ÷
ID, MT, OR, WA
Enter Now, Edits Allowed
x
Non-unique
User
None
–
–
–
Figure 11.2. Implementing a constraint imposed by a database oriented busi- ness rule.
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Categories of Business Rules 409
this constraint meaningfully in the logical design for two reasons: There
is no field in which to store the discount amount (the amount is a result
of a calculation, and calculated fields are not allowed in a table), and
there is no way to indicate the criterion used—the customer’s status—to
determine the discount. This is a rule that you must establish within the
physical design of the database or the design of the database application.
Although both types of business rules are important, you’ll focus on
database oriented business rules during this stage of the database-
design process.
Categories of Business Rules
It will be easier for you to understand and define business rules if you
divide them into two distinct categories: field specific and relationship
specific.
Field Specific Business Rules
Business rules under this category impose constraints on the elements
of a field specification for a particular field. The number of elements a
❖ Note The manner in which you actually define and establish application oriented business rules is a topic that is beyond the
scope of this book. Some RDBMSs provide tools that allow you to
implement common application oriented business rules relatively
easily; most RDBMSs will require you to write programming code
to implement and enforce these rules.
❖ Note Throughout the remainder of the book, I’ll refer to data- base oriented business rules simply as business rules.
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410 Chapter 11 Business Rules
given rule affects depends on the manner in which you define that rule.
For example, this rule only affects one element:
Order dates are to be displayed in long form, such as “January
10, 2003.”
This rule affects the Display Format element of the ORDER DATE field in
an ORDERS table. You establish this rule by modifying the Display For-
mat element of the field specifications for the ORDER DATE field to indi-
cate the manner in which the date should be displayed.
Here’s a rule that affects more than one element:
We must be able to store a zip code for our Canadian customers.
This rule affects the Data Type, Character Support, and Display Format
elements of the field specifications for the CUSTZIPCODE field in a CUS-
TOMERS table. Canadian zip codes include letters, so you must make
the following modifications to these elements in order to impose the
constraints defined by this rule:
1. Change the Data Type setting to “Alphanumeric.”
2. Include “Letters” under the Character Support element.
3. Modify the Display Format element to ensure that the letters in
Canadian zip codes will be capitalized.
Figure 11.3 shows the modified Physical Elements section of CUSTZIP-
CODE’s field specifications.
Relationship Specific Business Rules
These types of business rules impose constraints that affect the charac-
teristics of a relationship. For instance, assume you’re working with the
tables and relationships in Figure 11.4.
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Categories of Business Rules 411
Say you determine that there must be a limit to the number of students
for each class and you define the following business rule:
Each class must have a minimum of 5 students, but cannot
have more than 20.
This business rule affects the degree of participation between the
CLASSES and STUDENT CLASSES tables. You enforce the constraint
this rule defines by modifying the relationship diagram to show that a
single record in the CLASSES table must be related to at least 5—but no
more than 20—records in the STUDENT CLASSES table. (Depending on
Figure 11.3. Establishing a field specific business rule for CUSTZIPCODE.
Physical Elements
Length:
Decimal Places:
Input Mask:
Display Format:
Data Type: Character Support:
Numbers (0–9)
.Keyboard ( , / $ # %)
Special ( © ® ™ ∑ π)
x6 Not Applicable x
Alphanumeric
Letters (A–Z)
Uppercase letters where applicable.
Not Applicable
Figure 11.4. Tables and relationships from a school database.
Student Classes
Student ID
Class ID
ClassesStudents
Student ID StudFirst Name StudLast Name StudStreet Address
StudCity StudState StudZipcode StudHome Phone StudEmail Address Social Security Number
CPK/FK
CPK/FK
FK
PKPK Class ID
Instructor ID
Class Name
Class Description
Category
(1,1) (1,1)
(0,N)
(R)(R)
(0,N)
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412 Chapter 11 Business Rules
your point of view, you could also infer from this business rule that the
type of participation for the STUDENT CLASSES table is now manda-
tory. You can enter a new class or keep an existing class in the
CLASSES table if and only if there are at least five students registered
for that class.) Figure 11.5 shows the modification you must make to
the diagram in order to establish the business rule.
Defining and Establishing Business Rules
You’ll define and establish business rules for the database during this
stage of the design process. Remember that you must base these rules
on the manner in which your organization perceives and uses its data,
which (as you well know) will depend on the way the organization func-
tions or conducts its business. The best approach to this task is to de-
fine and establish the field specific business rules first, followed by the
relationship specific business rules. This approach helps you to remain
focused on the type of rule you’re defining. It also keeps you from jump-
Figure 11.5. Establishing a relationship specific business rule.
Student Classes
Student ID
Class ID
ClassesStudents
Student ID StudFirst Name StudLast Name StudStreet Address StudCity StudState StudZipcode StudHome Phone StudEmail Address Social Security Number
CPK/FK
CPK/FK
FK
PKPK Class ID
Instructor ID
Class Name
Class Description
Category
(1,1) (1,1)
(0,N)
(R)(R)
(5,20)
Modification made to the Degree of Participation for
the CLASSES table
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Defining and Establishing Business Rules 413
ing back and forth between different types of business rules, which can
often lead to confusion and some amount of frustration.
Working with Users and Management
Once again, you’ll work with the representative group of users and man-
agement. Schedule new meetings with them so that you can work to-
gether to define and establish the appropriate business rules for the
database. Working as a group enables you to make certain that the con-
straints imposed by the business rules you define are meaningful and
that there is no confusion or ambiguity as to the necessity of imposing
each constraint. If you or anyone in the group has some doubt about a
constraint, you can discuss the effect it will have on the field or relation-
ship involved and the advantages and disadvantages of imposing the
constraint. Then, you can decide whether to keep the rule or disregard
it completely based on the results of your discussion.
Defining and Establishing Field Specific Business Rules
Begin the process of establishing business rules for the database by
working on field specific rules. You define and establish each rule using
these steps:
1. Select a table.
2. Review each field and determine whether it requires any
constraints.
3. Define the necessary business rules for the field.
4. Establish the rules by modifying the appropriate field specification
elements.
5. Determine what actions test the rule.
6. Record the rule on a Business Rule Specifications sheet.
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Let’s now take a look at each step in greater detail.
Step 1: Select a Table
It doesn’t matter which table you start with because you’ll eventually
apply this procedure to every table within the database. If you choose a
table with a familiar structure, however, you can focus a little more on
learning the steps within the procedure. This extra effort will pay divi-
dends when you begin to work with tables containing fields that bear
closer attention and examination.
Think about the subject the table represents and then pose these
questions:
How does the organization use information based on or related
to this subject?
What relationships does this table have to itself or to other
tables in the database?
When necessary, consult the final table list and read the description for
this table, and refer to any relationship diagrams that incorporate this
table. The answers to these questions will be useful to you while you’re
defining rules for this table, and focusing on the table in this manner
prepares you for the next step.
Step 2: Review Each Field and Determine Whether It Requires Any Constraints
Examine the Field Specifications sheet for each field and determine
whether you should apply a constraint to any of its elements. Keep the
questions from Step 1 in mind as you review a given specification sheet,
and then pose this question:
Based on how the table is used within the database, is a con-
straint necessary for any element within this specification?
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Defining and Establishing Business Rules 415
If the answer is no, move on to the next field; otherwise, go on to the
next step. For example, assume you’re working with the CUSTCOUNTY
field in a CUSTOMERS table and you have just posed the question
about the need for a constraint. (Figure 11.6 shows the current Logical
Elements category for this field.)
You should move on to the next step if you receive an answer such as this:
“Well, the boss wants to begin tracking our customers by
county, so we must make certain we record a county for every
customer. In fact, we’ve just added Pierce County and Snohom-
ish County to our sales region, so it’ll be imperative that the
county names get recorded.”
Figure 11.6. Current settings for the Logical Elements category of the CUST- COUNTY field.
Logical Elements
Key Structure:
Non
Not Determined At This Time
Edit Rule:
Null Support: Nulls Allowed
Enter Now, Edits Not Allowed
Enter Later, Edits Allowed
Primary
AlternateForeign
Uniqueness: Unique
Required Value: No
Comparisons Allowed:
x x
Range of Values:
Default Value:
Values Entered By:
Operations Allowed:
Systemx
Key Type:
CompositeSimple
Enter Later, Edits Not Allowed
<> <=>=
Other Fields
Same Field =
Value Expression
<> <=>==
<> <=>==
All
All
Same Field
Other Fields Concatenation
All
All
+
+
x
x
Value Expression All Concatenation+ x
Concatenation
≠ ≠ ≠
÷ ÷ ÷
Enter Now, Edits Allowed
x
Non-unique
User
None
King, Kitsap
Allx x
x x
x x
Yes
No Nullsx
x
x
–
–
–
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416 Chapter 11 Business Rules
This response clearly is a yes, so you will go on to define business rules
for this field in the next step.
Step 3: Define the Necessary Business Rules for the Field
You define the appropriate business rules for the CUSTCOUNTY field by
identifying the constraints implied by the response in Step 2. Then you
transform each constraint into a rule.
The response in Step 2 suggests two possible constraints that you
should impose upon the CUSTCOUNTY field: A county name is required for
each customer, and the range of values for this field is limited to four
specific counties (the two currently on the field specification and the two
new counties indicated in the response). Here are two statements you
might use to begin transforming these constraints into business rules:
A county must be associated with each customer.
The only counties that can be entered into this field are King,
Kitsap, Pierce, and Snohomish.
Once you’ve defined the appropriate business rules, you can move on to
Step 4.
Step 4: Establish the Rules by Modifying the Appropriate Field Specification Elements
Establish each business rule you defined in Step 3 by modifying the ap-
propriate elements on the Field Specifications sheet. (Remember that
some rules may affect more than one element.) First, however, you must
identify which elements of the field specifications the rule affects. For
example, consider the first business rule you defined for the CUSTCOUNTY
field in Step 3:
A county must be associated with each customer.
You can deduce that the rule affects the Required Value, Null Support,
and Edit Rule elements because it explicitly states that a county “must
From the Library of Stephen Benoit
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Defining and Establishing Business Rules 417
be associated” with a customer. Now you can make the appropriate
modifications to these elements. In this particular case, you’ll set Re-
quired Value to “Yes,” Null Support to “No Nulls,” and Edit Rule to “En-
ter Now, Edits Allowed.”
As you can see, it’s important for you to examine each business rule
very carefully in order to determine which field specification elements
it’s going to affect. When you first begin to define business rules, it’s
best to have a Field Specifications sheet handy so that you can refer to
it as necessary. Many of the elements will come to mind more easily as
you become more experienced at establishing business rules.
Now, consider the next business rule in the example:
The only counties that can be entered into this field are King,
Kitsap, Pierce, and Snohomish.
This business rule affects the Range of Values element, and you’ll now
revise its setting to “King, Kitsap, Pierce, and Snohomish.” Figure 11.7
shows the revised Logical Elements category of the Field Specifications
sheet for the CUSTCOUNTY field.
Step 5: Determine What Actions Test the Rule
The constraint the business rule imposes is tested when you attempt to
perform one of three actions: inserting a record into the table or an en-
try into a field, deleting a record from the table or a value within a field,
or updating a field’s value. Now that you’ve established a business rule
and understand the constraint it will impose, determine what actions
test the rule by identifying when a violation of the rule is most likely to
occur. You can make this a relatively easy task by asking yourself the
following questions:
Will this rule be violated if I enter a new record into this table?
Will this rule be violated if I do not enter a new record into this table?
Will this rule be violated if I delete a record from this table?
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Will this rule be violated if I enter a value into this field?
Will this rule be violated if I do not enter a value into this field?
Will this rule be violated if I update the value of this field?
Will this rule be violated if I delete the value of this field?
Once you’ve determined which actions will trigger a violation of the rule,
make note of them; you’ll use them in the next step. This information
will also help you to establish this rule in the most effective manner
possible when you implement the database in your RDBMS.
In this case, the business rule for the CUSTCOUNTY field will be tested
when you try to insert a value into the field because the value must be
Figure 11.7. Revised settings for the Logical Elements category of the CUST- COUNTY field.
Logical Elements
Key Structure:
Non
Not Determined At This Time
Edit Rule:
Null Support: Nulls Allowed
Enter Now, Edits Not Allowed
Enter Later, Edits Allowed
Primary
AlternateForeign
Uniqueness: Unique
Required Value: No
Comparisons Allowed:
x
x
x
x
Range of Values:
Default Value:
Values Entered By:
Operations Allowed:
Systemx
Key Type:
CompositeSimple
Enter Later, Edits Not Allowed
<> <=>=
Other Fields
Same Field =
Value Expression
<> <=>==
<> <=>==
All
All
Same Field
Other Fields Concatenation
All
All
+
+
x
x
Value Expression All Concatenation+ x
Concatenation
≠ ≠ ≠
÷ ÷ ÷
Enter Now, Edits Allowed
x
Non-unique
User
None
King, Kitsap, Pierce, Snohomish
Allx x
x x
x x
Yes
No Nulls
–
–
–
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Defining and Establishing Business Rules 419
within a specific range of values. The rule will also be tested when you
try to delete a value in the field because the value cannot be null.
Step 6: Record the Rule on a Business Rule Specifications Sheet
You can document a given business rule for future reference by filling
out a Business Rule Specifications sheet. This is something you should
do for every rule, regardless of its type or category. The Business Rule
Specifications sheet provides three advantages:
1. It allows you to document every database oriented business rule.
This helps you ensure that you have appropriately defined and
properly established each rule.
2. It allows you to document every application oriented business rule.
Although you cannot establish this type of rule within the logical
design of the database, you can at least indicate its basic elements.
The information you document for this type of business rule will
prove invaluable to you when you implement the database within
your RDBMS or when you create the application program that peo-
ple will use to work with the database.
3. It provides a standard method for recording all business rules. Busi-
ness rules are easier to track and maintain if you record them in a
consistent manner. Using a uniform format also makes it easier for
you to troubleshoot business rules; every aspect of the rule ap-
pears on the specification sheet.
The Business Rule Specifications sheet contains the following items:
• Statement. This is the text of the business rule itself. It should be
clear and succinct and should convey the required constraints
without any confusion or ambiguity. Here’s an example of a well-
framed statement:
A booking agent cannot be assigned to more than 25
entertainers.
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420 Chapter 11 Business Rules
• Constraint. This is a brief explanation of how the constraint ap-
plies to the tables and fields. For instance, you can use the follow-
ing explanation for the constraint imposed by the business rule in
the preceding example:
A single record in the AGENTS table can be associated with
no more than 25 records in the ENTERTAINERS table.
• Type. Here is where you indicate whether the rule is database
oriented or application oriented.
• Category. This is where you indicate whether the rule is field
specific or relationship specific.
• Test on. Here is where you indicate which actions (insert, delete,
update) will test the constraint the business rule imposes.
• Structures Affected. Depending on the type of business rule, the
constraint will affect either a field or a relationship. This is where
you designate the name of the field(s) the rule will affect or the
name of the table(s) involved in the relationship that the rule
affects.
• Field Elements Affected. A business rule that pertains to a field
can affect one or more elements of that field’s specifications. This
is where you indicate the elements the rule affects.
• Relationship Characteristics Affected. A business rule that per-
tains to a relationship will affect one or more of the relationship’s
characteristics. Here is where you indicate the characteristics
that the rule affects.
• Action Taken. Here you indicate the modifications you’ve made to
the elements of a field specification or to a relationship diagram. It
is very important that the statement you enter here be as clear
and unambiguous as possible. Should a problem occur as a
result of enforcing this business rule, this statement serves as
accurate documentation of the steps you have taken to establish
From the Library of Stephen Benoit
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Defining and Establishing Business Rules 421
the rule. You can use this statement to make certain that these
steps were actually carried out and that the rule has been prop-
erly established.
Now, fill out a Business Rule Specifications sheet for the rule you estab-
lished in Step 4. Figure 11.8 shows a completed Business Rule Specifi-
cations sheet that documents the business rules you established for the
CUSTCOUNTY field.
Defining and Establishing Relationship Specific Business Rules
After defining and establishing field specific business rules, the next or-
der of business is to tackle relationship specific business rules. The pro-
cedure for performing this task involves the following steps:
1. Select a relationship.
2. Review the relationship and determine whether it requires any
constraints.
3. Define the necessary business rules for the relationship.
4. Establish the rule by modifying the appropriate relationship
characteristics.
5. Determine what actions will test the rule.
6. Record the rule on a Business Rule Specifications sheet.
As you can see, this procedure is similar to the one you used for field
specific business rules. Now, let’s take a look at each step in more detail.
❖Note You can apply this entire procedure to both self-referencing and dual-table relationships. I’ve based the remainder of the dis-
cussion on a dual-table relationship, however, because it is the type
of relationship you are likely to work with the majority of the time.
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422 Chapter 11 Business Rules
Figure 11.8. An example of a Business Rule Specifications sheet.
Action Taken
Structures Affected
Field Names:
Table Names:
Rule Information
Statement:
Constraint:
Test On: Insert
Delete
x x
UpdateCategory: Field Specific
Relationship Specific
xType: Database Oriented Application Oriented
x
Field Elements Affected
Logical Elements
Key Structure
Edit Rule
Null Support
Uniqueness
Required Value
Comparisons Allowed
x
x Range of Values Default Value
Values Entered By
Operations Allowed
Key Type
x
Physical Elements
Length
Input MaskDecimal Places
Character Support Display Format
Data Type
Relationship Characteristics Affected
Degree of ParticipationType of ParticipationDeletion Rule
CUST COUNTY
Required Value was set to “Yes,” Null Support was set to “No Nulls,” and Edit Rule was set to “Enter Now, Edits Allowed.”
A county must be associated with each customer.
An entry must be made into the CustCounty field; it cannot be Null.
BUSINESS RULE SPECIFICATIONS
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Defining and Establishing Business Rules 423
Step 1: Select a Relationship
Which relationship you choose is a relatively trivial matter because
you’ll eventually apply this procedure to every relationship anyway.
Once you select a specific relationship, review its relationship diagram.
Then think about what the tables represent and why they are related
and pose the following questions:
What kind of information do these tables provide?
Why is the relationship between these two tables important?
The answer to these questions will help you define any necessary busi-
ness rules for the relationship, and keeping them in mind will prepare
you for the next step.
Step 2: Review the Relationship and Determine Whether It Requires Any Constraints
Briefly review each relationship characteristic and keep its current set-
ting in mind. Then examine the relationship as a whole and determine
whether it requires some form of constraint. As you review the relation-
ship, remember the answers to the questions you posed in Step 1. You
now pose a question such as this to help you determine whether a con-
straint is necessary:
Is there a need to impose some type of limitation on this rela-
tionship based on the way the organization functions or
conducts its business?
If the answer is yes, then go to the next step; otherwise, review the next
relationship and perform this step once again. For example, assume
you’re designing a database for a small dance studio, and you’re work-
ing with the relationship between the INSTRUCTORS and INSTRUCTOR
CLASSES tables in Figure 11.9.
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424 Chapter 11 Business Rules
Now, pose a question to help you determine whether the relationship re-
quires a constraint.
Is there a need to impose some type of limitation on this rela-
tionship based on the way the dance studio functions or
conducts its business?
Move to the next step if you receive an answer such as this:
Yes, there is. We require all instructors to teach at least one
class. We limit them, however, to teaching no more than eight
classes.
You’ll use this response as the basis of a business rule in the next step.
Step 3: Define the Necessary Business Rules for the Relationship
Next, define an appropriate business rule based on the response you re-
ceived in Step 2. Identify the constraint the response implies and then
transform it into a business rule. For example, you can infer two con-
straints from the response: The minimum number of classes an instruc-
Figure 11.9. A relationship diagram for tables from a dance studio database.
Instructor Classes
Instructor ID
Class ID
(1,1) (1,1)
(0,N)
(R)(R)
Instructors
CPK/FK
CPK/FK (0,N)
PK
Classes
PKClass ID
Class Name
Class Description
Category
Instructor ID InstFirst Name InstLast Name InstStreet Address InstCity InstState InstZipcode InstHome Phone InstEmail Address Date Hired
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Defining and Establishing Business Rules 425
tor can teach is one, and the maximum number is eight. Transform
these constraints into a business rule by composing a statement such
as this one:
An instructor must teach one class, but no more than eight
classes.
After you’ve defined the rule, continue with the next step.
Step 4: Establish the Rule by Modifying the Appropriate Relationship Characteristics
Establish the business rule you just defined by modifying the appropri-
ate characteristics in the relationship diagram. Before you make any
modifications, consider the business rule statement once again and
identify which relationship characteristics the rule affects.
An instructor must teach one class, but no more than eight
classes.
The constraint affects the number of classes an instructor can teach,
so you modify the degree of participation characteristic of the IN-
STRUCTOR CLASSES table by setting it to “(1,8).” This rule also af-
fects the type of participation characteristic of the INSTRUCTOR
CLASSES table. You must set the table’s type of participation to “Man-
datory” because a single record in the INSTRUCTORS table must be
associated with at least one record in the INSTRUCTOR CLASSES ta-
ble. Figure 11.10 shows the revised relationship diagram with your
modifications.
Step 5: Determine What Actions Will Test the Rule
As you know, the constraint the business rule imposes is tested when
you attempt to insert, delete, or update a table record or field value. Now
that you’ve established the business rule and understand how it affects
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426 Chapter 11 Business Rules
the relationship, determine what actions test the rule by identifying
when a violation of the rule is most likely to occur. Use the following
questions to help you make your decision:
Are there circumstances under which this rule will be violated if
I enter a new record into this table?
Will this rule be violated if I do not enter a new record into this
table?
Will this rule be violated if I delete a record from this table?
Figure 11.10. The revised relationship diagram that establishes the new busi- ness rule.
Instructor Classes
Instructor ID
Class ID
(1,1) (1,1)
(R)(R)
Instructors
CPK/FK
CPK/FK (0,N)
PK
Classes
PKClass ID
Class Name
Class Description
Category
Instructor ID InstFirst Name InstLast Name InstStreet Address InstCity InstState InstZipcode InstHome Phone InstEmail Address Date Hired
Modification made to the Degree of Participation for the INSTRUCTOR CLASSES table
Modification made to the Type of Participation for the
INSTRUCTOR CLASSES table
(1,8)
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Defining and Establishing Business Rules 427
Once you’ve determined which actions will trigger a violation of the rule,
make note of them; you’ll use them in the next step. This information
will also help you to establish this rule in the most effective manner
possible when you implement the database in your RDBMS.
Here’s an important point to note: When you determine that a rule will
be violated when you attempt to delete a record, then you must alter the
current deletion rule for the relationship accordingly or add a new dele-
tion rule to the relationship.
You learned in Chapter 10 that you don’t need to worry about deleting
records in the child table of a relationship because there can be no ad-
verse effects from doing so. We must now amend this assertion by stat-
ing that an exception occurs when deleting a record in the child table
would violate a required business rule. You handle this exception by es-
tablishing a Restrict deletion rule for the child table. Make absolutely
certain that you keep this in mind as you’re determining when a rule
will be tested.
The new business rule for the dance studio database will be tested
when you attempt to insert a record into the INSTRUCTOR CLASSES ta-
ble; you can associate a maximum of only eight records with a particu-
lar instructor. The rule will also be tested when you attempt to delete a
record from the INSTRUCTOR CLASSES table; each instructor must be
associated with at least one class. As a result, you must establish a Re-
strict deletion rule for this table. Figure 11.11 shows the modifications
you’ve made to this relationship’s diagram.
Step 6: Record the Rule on a Business Rule Specifications Sheet
Finally, fill out a Business Rule Specifications sheet for the business
rule you established in Step 4. Figure 11.12 shows the completed Busi-
ness Rule Specifications sheet for your new rule.
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428 Chapter 11 Business Rules
Validation Tables
As you define field specific business rules, there will be instances in
which a rule imposes a constraint that defines a distinct set of valid val-
ues for a given field’s range of values. (This obviously affects the field’s
Range of Values element in its field specification.) This set of values
commonly comprises a relatively fixed number of entries, and the values
themselves will rarely change. If the number of entries is rather high,
however, you might discover that it’s going to be slightly difficult for you
to implement this rule. For example, you’ll probably run out of room
very quickly when you attempt to enumerate each of the values within
the Range of Values element on the Field Specifications sheet, and im-
plementing the entire set of values within the RDBMS could prove to be
somewhat complicated. You can avoid problems such as these by stor-
ing all of the values in a validation table.
Figure 11.11. Establishing a Restrict deletion rule for the INSTRUCTOR CLASSES table to support the new business rule.
Instructor Classes
Instructor ID
Class ID
(1,1) (1,1)
(R)(R)
Instructors
CPK/FK
CPK/FK (0,N)
PK
Classes
PKClass ID
Class Name
Class Description
Category
Instructor ID InstFirst Name InstLast Name InstStreet Address InstCity InstState InstZipcode InstHome Phone InstEmail Address Date Hired
New Restrict deletion rule added for the INSTRUCTOR CLASSES table
(1,8)
(R)
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Validation Tables 429
Figure 11.12. The completed Business Rule Specifications sheet for the new business rule.
Action Taken
Structures Affected
Field Names:
Table Names:
Rule Information
Statement:
Constraint:
Test On: Insert
Delete
x x
UpdateCategory: Field Specific
Relationship Specific
Type: Database Oriented
Application Oriented
x
Field Elements Affected
Logical Elements
Key Structure
Edit Rule
Null Support
Uniqueness
Required Value
Comparisons Allowed
Range of Values
Default Value
Values Entered By
Operations Allowed
Key Type
Physical Elements
Length
Input MaskDecimal Places
Character Support Display Format
Data Type
Relationship Characteristics Affected
Degree of ParticipationType of ParticipationDeletion Rule
The type of participation for the INSTRUCTOR CLASSES table was changed to Mandatory. The degree of participation for the INSTRUCTORS CLASSES table was changed to (1,8). A new Restrict deletion rule was added to the relationship for the INSTRUCTOR CLASSES table.
INSTRUCTORS, INSTRUCTOR CLASSES
An instructor must teach one class, but no more than eight (8) classes.
The participation of INSTRUCTORS within the relationship is Mandatory. Also, a single record in INSTRUCTORS can be related to only eight (8) records in INSTRUCTOR CLASSES.
xx x
x
BUSINESS RULE SPECIFICATIONS
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430 Chapter 11 Business Rules
What Are Validation Tables?
As you learned in Chapter 3, a validation table (also known as a lookup
table) stores data that you specifically use to implement data integrity.
You won’t often insert, update, or delete any records within the table
once you populate the table with the data you require. Validation tables
usually (but not always) comprise two fields: The first acts as the pri-
mary key and is what you’ll use to help you enforce data integrity, and
the second is simply a non-key field that stores a set of values required
by some other field in the database. Figure 11.13 shows two examples
of validation tables.
In this section, you’ll learn how to use the primary key field to help en-
force a business rule. You’ll learn how to use the non-key field later in
Chapter 12.
Figure 11.13. Examples of validation tables.
Category
Architects
General Contractors
Attorneys
Computer Consultants
Category ID
60002
60003
60004
60001
Categories States
State
AL
AK
AR
CA
State Name
Alabama
Arizona
Arkansas
California
Primary Key Field
Non-Key Field
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Validation Tables 431
Using Validation Tables to Support Business Rules
When a business rule limits a field’s range of values, you can enforce
the constraint by using a validation table; the field will then draw its
values from an appropriate field in the validation table. Establishing
this type of rule involves two steps: defining a relationship between the
parent table of the field affected by the rule and the validation table and
making a modification to the Range of Values element of the field speci-
fications for the affected field in the parent table.
For example, assume you’re working with the SUPPSTATE field of a SUP-
PLIERS table, and you’ve defined the following business rule:
Any supplier we use must be based in one of the 11 contiguous
Western states, Alaska, or Hawaii.
You can see that this rule imposes a constraint on the SUPPSTATE field’s
range of values, limiting them to AK, AZ, CA, CO, HI, ID, MT, NM, NV, OR,
UT, WA, and WY. (According to the rule, you can’t use a supplier based in
some other state.) The easiest and most efficient way to establish this rule
is to store these values in a validation table called STATES and then use
the validation table as the source of the SUPPSTATE field’s range of values.
Consider the tables in Figure 11.14. (Note the new symbol that is used
to represent a validation table.) The SUPPLIERS table stores all the req-
uisite data on the SUPPLIERS engaged by the organization, and the
STATES table is a new validation table that will store the names and ab-
breviations of the specified STATES.
Your first order of business (no pun intended) is to establish a relation-
ship between these tables. As you can see, there is a one-to-many rela-
tionship between them—a single record in STATES can be associated
with one or more records in SUPPLIERS, but a single record in SUPPLI-
ERS will be associated with only one record in STATES. You already
know that you establish a one-to-many relationship by taking a copy of
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432 Chapter 11 Business Rules
the parent table’s primary key and incorporating it within the structure
of the child table where it becomes a foreign key. Although the SUPPLI-
ERS table already has a field named SUPPSTATE, you’ll replace it with the
STATE field from the STATES validation table. (This is a reasonable mod-
ification because it is in accordance with the Elements of the Ideal Field
and is consistent with the manner in which you establish one-to-many
relationships.) Figure 11.15 shows the new relationship diagram for
these two tables.
Figure 11.14. The SUPPLIERS table and the STATES validation table.
Suppliers
PKSupplier ID
SuppName
SuppFax Number
Supp Address
SuppCity
SuppState
SuppZipcode
SuppPhone Number
State
State Name
States
PK
Figure 11.15. A relationship diagram for the SUPPLIERS and STATES tables.
Suppliers
PKSupplier ID
SuppName
SuppFax Number
Supp Address
SuppCity
State
SuppZipcode
SuppPhone Number
State
State Name
States
PK
(1,1)
(0,N)
(R)
FK
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Validation Tables 433
Now that the STATE field is a foreign key in the SUPPLIERS table, make
certain that it conforms to the Elements of a Foreign Key (as outlined in
Chapter 10) and set its field specification in the appropriate manner.
Then set the relationship’s characteristics in this manner:
• Deletion Rule. Define a Restrict deletion rule for this relationship.
You do not want to delete a state in the STATES table that is being
referenced by records in the SUPPLIERS table.
• Type of Participation. Designate an Optional type of participation
for the SUPPLIERS table and a Mandatory type of participation for
the STATES table. Although it’s unnecessary for the SUPPLIERS
table to contain any records before you can enter a new record in
the STATES table, there must be at least one record in the STATES
table before you can enter records into the SUPPLIERS table.
• Degree of Participation. Assign a (1,1) degree of participation for
the STATES table; as you already know, there must be at least
one record in the STATES table before you can enter records into
the SUPPLIERS table. Assign a (0,N) degree of participation for the
SUPPLIERS table; any number of records in this table can be
associated with a particular record in the STATES table.
Next, modify the Range of Values element of the field specification for
the STATE field in the SUPPLIERS table using a setting such as this:
Any value within the STATE field of the STATES table.
Figure 11.16 shows the settings you’ve made within the Logical Ele-
ments category of the Field Specifications sheet for this field.
Now you must decide which actions test the rule. When you use a valida-
tion table to enforce a business rule, you typically want to test the rule
when a user attempts to insert a new value into the field or update an ex-
isting value within the field. In either case, a violation will occur when the
user attempts to enter a value that does not exist in the validation table.
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434 Chapter 11 Business Rules
Finally, fill out a Business Rule Specifications sheet for the business
rule you’ve just established. Be sure to indicate the modifications you’ve
made to both the field and the new relationship. Figure 11.17 shows the
completed Business Rule Specifications sheet for your new rule.
Reviewing the Business Rule Specifications Sheets
After you’ve established the business rules you believe to be appropriate,
review their specifications sheets. Carefully examine each specification
sheet and make certain that you’ve properly established the rule and
Figure 11.16. Setting the Logical Elements category for the STATE foreign key field in the SUPPLIERS table.
Logical Elements
Key Structure:
Non
Not Determined At This Time
Edit Rule:
Null Support: Nulls Allowed
Enter Now, Edits Not Allowed
Enter Later, Edits Allowed
Primary
Alternate
Uniqueness: Unique
Required Value: No
Comparisons Allowed:
x
x
x
x
Range of Values:
Default Value:
Values Entered By:
Operations Allowed:
Systemx
Key Type:
CompositeSimple
Enter Later, Edits Not Allowed
<> <=>=
Other Fields
Same Field =
Value Expression
<> <=>==
<> <=>==
All
All
Same Field
Other Fields Concatenation
All
All
+
+
x
x
Value Expression All Concatenation+ x
Concatenation
≠ ≠ ≠
÷ ÷ ÷
Enter Now, Edits Allowedx
User
None
Any value within the State field of the STATES table
Allx x
Yes
No Nulls
Non-unique
Foreign
xx
–
–
–
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Reviewing the Business Rule Specifications Sheets 435
Figure 11.17. A completed Business Rule Specifications sheet for the new busi- ness rule.
Field Names:
Table Names:
Statement:
Constraint:
Test On: Insert
Delete
x UpdateCategory: Field Specific Relationship Specific
Type: Database Oriented
Application Oriented
x
Logical Elements
Key Structure
Edit Rule
Null Support
Uniqueness
Required Value
Comparisons Allowed
Range of Values
Default Value
Values Entered By
Operations Allowed
Key Type
Physical Elements
Length
Input MaskDecimal Places
Character Support Display Format
Data Type
Degree of ParticipationType of ParticipationDeletion Rule xx x
x
Any supplier we use must be based in one the eleven (11) contiguous Western states, Alaska, or Hawaii.
Entries for the State field in the SUPPLIERS table are limited to existing values of the State field in the STATES table.
SUPPLIERS, STATES
STATE
The Range of Values was set to “Any value within the State field of the STATES table.” The type of participation for each table was changed: STATES is Mandatory; SUPPLIERS is Optional. The degree of participation for each table was changed: SUPPLIERS is (0,N); STATES is (1,1). A Restrict deletion rule was defined for the relationship between SUPPLIERS and STATES.
x
x
BUSINESS RULE SPECIFICATIONS
Action Taken
Structures Affected
Rule Information
Field Elements Affected
Relationship Characteristics Affected
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436 Chapter 11 Business Rules
that you’ve clearly marked all of the appropriate areas on the sheet. If
you find an error, make the necessary modifications and review it once
more. Repeat this process until you’ve reviewed every business rule.
Business rules are an important component of the database. They con-
tribute to overall data integrity and impose integrity constraints that are
specific to the organization. As you’ve seen, these rules help to ensure
the validity and consistency of the data according to the manner in
which the organization functions or conducts its business. Additionally,
these rules will eventually influence the manner in which you imple-
ment the database within your RDBMS and how you design and develop
end-user application programs for the database.
It’s important to understand that you will revisit these rules quite often.
As you review the final structure, for example, you may determine that
additional business rules are necessary. You may discover that some of
the rules will not provide the results you had initially envisioned, so
you’ll need to modify them. It’s also possible for you to determine that
some of the rules aren’t necessary after all. (In this instance, be abso-
lutely sure to examine the rules carefully before you remove them.)
Keep in mind that the business rules you define now are bound to re-
quire modifications in the future; you will most likely need to add busi-
ness rules in due course because of changes in the way the organization
functions or conducts its business. The need to modify existing busi-
ness rules or develop new ones is quite normal—the organization inevi-
tably grows and matures, and so does the manner in which it acts upon
or reacts to external forces. These forces affect the manner in which the
organization perceives and uses its data, which, in turn, changes the
nature of the organization’s business-rule requirements.
The task of defining and establishing business rules is—as are so many
other tasks within the database-design process—ongoing. Don’t be dis-
couraged if you have to perform this task several times. Your efforts will
pay great dividends in the long run.
From the Library of Stephen Benoit
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Case Study 437
Now it’s time to establish business rules for Mike’s database. You
schedule a meeting with Mike and his staff to review the tables and rela-
tionships in their database. The first order of business is to define and
establish field specific business rules.
You start the process by reviewing the PRODUCTS table. As you exam-
ine each field, you determine whether it requires any constraints. When
you come upon the CATEGORY field, you remember that there was some
question regarding its range of values. (Refer to the Case Study in Chap-
ter 9.) You discuss this issue once again with Mike and his staff, and
you finally come to a consensus on a distinct list of categories. Mike
then decides that the values for the CATEGORY field should be limited to
those on this list to make certain that the staff does not arbitrarily in-
vent new categories. Based on Mike’s decision, you define an appropri-
ate business rule to establish the constraint.
Invalid product categories are not allowed.
There are a number of items in the list of possible categories, so you de-
cide that the best way to establish this rule is to use a validation table.
You create a new table called CATEGORIES and then establish a rela-
tionship between it and the PRODUCTS table. Next, you diagram the re-
lationship and set the relationship’s characteristics in the appropriate
manner. Figure 11.18 shows the results of your work.
Here are the settings you used for the relationship’s characteristics:
• There is a Restrict deletion rule for the relationship.
• The CATEGORIES table has a mandatory type of participation.
• The PRODUCTS table has an optional type of participation.
• The CATEGORIES table has a (1,1) degree of participation.
• The PRODUCTS table has a (0,N) degree of participation.
CASE STUDY
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438 Chapter 11 Business Rules
Remember that by establishing this relationship, you’ve replaced the ex-
isting CATEGORY field in the PRODUCTS table with a copy of the CATEGORY
ID field from the new CATEGORIES table. You must now make certain
that the CATEGORY ID field in the PRODUCTS table conforms to the Ele-
ments of a Foreign Key and then make the appropriate modifications to
its field specification. Finally, set the field’s Range of Values element to
something such as this:
Any value within the CATEGORY ID field in the CATEGORIES table
Figure 11.19 shows the settings you’ve made to the Logical Elements
category of the field specifications for the CATEGORY ID field in the PROD-
UCTS table.
Now you must decide when the rule should be tested. As you already
know, you typically want to test a rule established with a validation ta-
ble if the user attempts to insert a value into the field or update an ex-
isting value within the field.
Finally, you complete a Business Rule Specifications sheet for this new
business rule. This specification sheet will reflect the modifications
Figure 11.18. The relationship diagram for the PRODUCTS and CATEGORIES tables.
Products
PK
Categories
PK
(1,1)
(R)
(0,N)
Category ID
CategoryDescription
Product Number
ProdDescription
ProdName
Retail Price
Wholesale Price
Category ID FK
From the Library of Stephen Benoit
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Case Study 439
you’ve made to the field specifications for the CATEGORY ID field, as well
as the characteristics of the relationship between the CATEGORIES and
PRODUCTS tables. Figure 11.20 shows the completed Business Rule
Specifications sheet.
You repeat this process for the remaining fields in this table and for the
fields in the remaining tables. After you’re finished, you move on to the
next task.
The next order of business is to establish relationship specific business
rules. You begin by reviewing the relationship between the EMPLOYEES
and INVOICES tables, and you review the relationship diagram to deter-
mine whether the relationship requires any constraints. Everything
Figure 11.19. Logical Elements settings for the CATEGORY ID foreign key field in the PRODUCTS table.
Logical Elements
Key Structure:
Non
Not Determined At This Time
Edit Rule:
Null Support: Nulls Allowed
Enter Now, Edits Not Allowed
Enter Later, Edits Allowed
Primary
Alternate
Uniqueness: Unique
Required Value: No
Comparisons Allowed:
x
x
x
x
Range of Values:
Default Value:
Values Entered By:
Operations Allowed:
Systemx
Key Type:
CompositeSimple
Enter Later, Edits Not Allowed
<> <=>=
Other Fields
Same Field =
Value Expression
<> <=>==
<> <=>==
All
All
Same Field
Other Fields Concatenation
All
All
+
+
x
x
Value Expression All Concatenation+ x
Concatenation
≠ ≠ ≠
÷ ÷ ÷
Enter Now, Edits Allowedx
User
None
Any value within the Category ID field in the CATEGORIES table
Allx x
x x
Yes
No Nulls
Non-unique
Foreign
xx
x
–
–
–
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Figure 11.20. The completed Business Rule Specifications sheet for the new business rule.
Field Names:
Table Names:
Statement:
Constraint:
Test On: Insert
Delete
x UpdateCategory: Field Specific Relationship Specific
Type: Database Oriented
Application Oriented
x
Logical Elements
Key Structure
Edit Rule
Null Support
Uniqueness
Required Value
Comparisons Allowed
Range of Values
Default Value
Values Entered By
Operations Allowed
Key Type
Physical Elements
Length
Input MaskDecimal Places
Character Support Display Format
Data Type
Degree of ParticipationType of ParticipationDeletion Rule xx x
x
PRODUCTS, CATEGORIES
CATEGORY ID
x
x
The Range of Values was set to “Any value within the Category ID field of the CATEGORIES table.” The type of participation for each table was changed: PRODUCTS is Optional; CATEGORIES is Mandatory. The degree of participation for each table was changed: PRODUCTS is (0,N); CATEGORIES is (1,1). A Restrict deletion rule was defined for the relationship between PRODUCTS and CATEGORIES.
Entries for the Category ID field in the CATEGORIES table are limited to existing values of the Category ID field in the CATEGORIES table.
Invalid product categories are not allowed.
Action Taken
Structures Affected
Rule Information
Field Elements Affected
Relationship Characteristics Affected
BUSINESS RULE SPECIFICATIONS
From the Library of Stephen Benoit
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Case Study 441
seems to be in order, so you move to the relationship between the VEN-
DORS and PRODUCTS tables. Figure 11.21 shows the relationship dia-
gram for these tables.
As you and Mike discuss whether you should impose any constraints
on this relationship, Mike determines that there should be a constraint
on the PRODUCTS table. He wants to make sure that every vendor in
the VENDORS table is associated with at least one product; he figures
that it’s unnecessary to keep data on a vendor who’s not supplying him
with any products. So you define the following business rule for this
constraint:
Every vendor must supply at least one product.
Now you establish the rule by modifying the appropriate relationship
characteristics. You begin by designating a Mandatory type of participa-
tion and assigning a (1,N) degree of participation to the PRODUCTS ta-
ble. You then define a Restrict deletion rule for the relationship based
on the PRODUCTS table; this will keep you from accidentally deleting
the only product associated with a given vendor. Figure 11.22 shows the
results of your modifications.
Figure 11.21. The relationship diagram for the VENDORS and PRODUCTS tables.
Vendors
PK
(1,1)
(0,N)
(R)
Products
PKProduct Number
ProdDescription
ProdName
Category ID
Retail Price
Wholesale Price
Vendor ID
Vendor ID
VendName
VendFax Number
Vend Address
VendCity
VendState
VendZipcode
VendPhone Number
FK
FK
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442 Chapter 11 Business Rules
You already know that this type of business rule will be tested when a
user attempts to insert a record into or delete a record from the PROD-
UCTS table, so you complete this process by filling out a Business
Rule Specifications sheet for this rule. Figure 11.23 shows the com-
pleted specification sheet.
Now you repeat this process for the remaining relationships. When
you’re finished, the process is complete and you’re ready for the next
stage of the database-design process.
Summary
This chapter opened with a definition of business rules. You learned
that a business rule is a constraint imposed on a field or a relationship
that is based on the way the organization perceives and uses its data
and that it is derived from the manner in which the organization func-
tions or conducts its business. You now know that there are two major
types of business rules: database oriented and application oriented. Al-
though our focus here is on database oriented business rules, you
Figure 11.22. The revised relationship diagram for the VENDORS and PROD- UCTS tables.
Vendors
PK
(1,1)
(R)
Products
PKProduct Number
ProdDescription
ProdName
Category ID
Retail Price
Wholesale Price
Vendor ID
Vendor ID
VendName
VendFax Number
Vend Address
VendCity
VendState
VendZipcode
VendPhone Number
FK
FK (1,N)
(R)
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Figure 11.23. A completed Business Rule Specifications sheet.
Field Names:
Table Names:
Statement:
Constraint:
Test On: Insert
Delete
x UpdateCategory: Field Specific Relationship Specific
Type: Database Oriented
Application Oriented
x
Logical Elements
Key Structure
Edit Rule
Null Support
Uniqueness
Required Value
Comparisons Allowed
Range of Values
Default Value
Values Entered By
Operations Allowed
Key Type
Physical Elements
Length
Input MaskDecimal Places
Character Support Display Format
Data Type
Degree of ParticipationType of ParticipationDeletion Rule xx x
x
VENDORS, PRODUCTS
x
The type of participation for PRODUCTS was changed to Mandatory. The degree of participation for PRODUCTS was changed to (1,N). A Restrict deletion rule was defined for the PRODUCTS table.
A single record in the VENDORS table must be associated with at least one record in the PRODUCTS table.
Every vendor must supply at least one product.
Action Taken
Structures Affected
Rule Information
Field Elements Affected
Relationship Characteristics Affected
BUSINESS RULE SPECIFICATIONS
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know that you can at least record the basic elements of application
oriented business rules for use later in the implementation process.
You then learned that database oriented business rules are divided into
two categories: field specific business rules, which affect the elements of
a field specification for a particular field; and relationship specific busi-
ness rules, which affect the characteristics of a relationship.
The chapter continued with a discussion of defining and establishing
business rules. Here you learned that you work with users and manage-
ment to define the business rules required by the organization. You also
learned that it is best to establish the field specific business rules first,
followed by the relationship specific business rules.
Next, you learned the steps necessary to define and establish each type
of business rule. You now know that, in general, you work with a field or
relationship, review the field or relationship in light of the rule to deter-
mine whether any constraints are necessary, define the appropriate
business rule, establish the rule by modifying the appropriate field
specification elements or relationship characteristics, decide which ac-
tions test the rule, and then complete a Business Rule Specifications
sheet for the rule.
The chapter continued with a discussion of the elements of the Busi-
ness Rule Specifications sheet, and how each element on the sheet is
defined. As you now know, using Business Rule Specifications sheets
allows you to document all of your rules and provides you with a stan-
dard method for recording and reviewing them.
We closed the chapter by discussing validation tables. You learned that
you can create and use a validation table to support a business rule
that limits the range of values for a particular field. In this manner, the
validation table helps to enforce data integrity. You also learned that
you need to establish new relationships when you use validation tables
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Review Questions 445
and that these relationships have the same types of characteristics as
any other types of relationships in the database.
Review Questions
1. What is a business rule?
2. Name the two major types of business rules.
3. Can you establish application oriented business rules within the
logical design of the database?
4. What are the two categories of database oriented business rules?
5. What is a field specific business rule?
6. When is a business rule tested?
7. How do you document a business rule?
8. State two advantages a Business Rule Specifications sheet
provides.
9. What is the purpose of the Action Taken section of a Business Rule
Specifications sheet?
10. What is the purpose of a validation table?
11. What is the typical structure of a validation table?
12. What is the association between a business rule and a validation
table?
13. Why should you review all of your completed Business Rule Speci-
fications sheets?
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12 Views
There is no object on earth which cannot be looked at from a cosmic point of view.
—FYODOR MIKHAYLOVICH DOSTOYEVSKY
Topics Covered in This Chapter
What Are Views?
Anatomy of a View
Determining and Defining Views
Case Study
Summary
Review Questions
What Are Views?
As you learned in Chapter 3, a view is a virtual table composed of fields
from one or more tables in the database; it can also include fields from
other views. The tables and views that comprise a given view are known
as the view’s base tables. A view is “virtual” because it draws data from
base tables rather than storing data on its own. In fact, the only infor-
mation about a view that is stored in the database is its structure; the
RDBMS rebuilds and “repopulates” the view every time you access the
view in some manner. Many major RDBMS programs support views, but
some (such as Microsoft Access) refer to them as saved queries. Your
specific RDBMS program will determine whether you refer to this object
as a query or a view.
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Views enable you to see the information in your database from many dif-
ferent aspects, providing you with a great amount of flexibility when you
work with your data. You can create views in a variety of ways, and they
are especially useful when you base them on multiple related tables.
There are several reasons why you should define and use views in your
database.
• You can use them to work with data from multiple tables simulta-
neously. During the database-design process, you established re-
lationships between various pairs of tables bearing one-to-many
or many-to-many relationships to each other. (Recall that you re-
solved the many-to-many relationships via linking tables.) A view
provides the mechanism that allows you to work with data from
two or more related tables simultaneously.
• They reflect the most current information. Because the RDBMS re-
builds and repopulates the view every time you access it, the in-
formation displayed by the view exhibits the most recent changes
to the data in its base tables.
• You can customize them to the specific needs of an individual or
group of individuals. You can build a view to suit any set of re-
quirements, such as providing the data for a particular report or
❖ Note Although every major database vendor supports the view I’ve just described, several vendors are now supporting what is
known as an indexed (or materialized) view. An indexed view is dif-
ferent from a regular view in that it does store data, and its fields
can be indexed to improve the speed at which the RDBMS pro-
cesses the view’s data. A full discussion of indexed views is beyond
the scope of this book because it is a vendor-specific implementa-
tion issue. However, you should research this topic further if you
are working with a client/server or mainframe RDBMS program.
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Anatomy of a View 449
providing a means of examining specific information that is com-
mon to several departments within an organization.
• You can use them to help enforce data integrity. You can define a
validation view that works in the same manner as a validation ta-
ble—its purpose is to provide a valid range of values for a given
field in the database.
• You can use them for security or confidentiality purposes. You can
determine what data is available to a particular user or group of
users by defining a view on select fields from the view’s base tables.
Define your views carefully and skillfully, and they will become a valu-
able asset after you’ve implemented the database within your RDBMS.
Anatomy of a View
There are three types of views (data, aggregate, validation) that you can
define as you design the logical structure of the database and two types
of views (materialized and partitioned) that you can define as you imple-
ment your database within an RDBMS. The ability to define the latter
two types of views and the manner in which you do so are highly depen-
dent upon your RDBMS, so they are beyond the scope of this book. We
will, therefore, focus our attention on the first three types of views.
Data View
You use this type of view to examine and manipulate data from a single
base table or multiple base tables.
Single-Table Data View
Although you could use all of the fields from the base table to build this
type of view, you’ll usually just use selected fields. (Building a view using
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all of the base table’s fields would simply produce a virtual copy of the
base table.) For example, say you want to make a list of employee names
and phone numbers available to everyone in the organization. You can
construct an EMPLOYEE PHONE LIST view based on the EMPLOYEES
table using just the EMPLOYEE ID, EMPFIRST NAME, EMPLAST NAME, and EMP-
PHONE NUMBER fields. Figure 12.1 shows a diagram of this particular view.
(Note the new symbol used to indicate a view.)
Your RDBMS will rebuild and repopulate the EMPLOYEE PHONE LIST
view each time you access it, and the view will reflect the latest changes
you’ve made to the data in the EMPLOYEES table. Figure 12.2 shows
how an RDBMS will typically display the data within a view. Note that
the view’s appearance is quite similar to that of a table; this is yet an-
other reason why a view is known as a “virtual table.”
Figure 12.1. The EMPLOYEE PHONE LIST view.
Employees
PKEmployee ID
EmpFirst Name
EmpLast Name
EmpStreet Address
EmpCity
EmpState
EmpZipcode
EmpHome Phone
Employee Phone List
EmpFirst Name EmpLast Name EmpPhone Number
Employee ID
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You can modify the data within a single-table data view at any time, and
the modifications you make will flow through the view and into the base
table. Keep in mind, however, that field specifications and business
rules will determine what types of modifications you can make to the
data. For example, you won’t be able to delete a last name in the EM-
PLOYEE PHONE LIST view if the Null Support element of the field spec-
ification for the EMPLAST NAME field is set to “No Nulls.”
Multitable Data View
As I mentioned at the beginning of this section, you can define a data
view using two or more tables. The only requirement is that the tables
you use to create the view must bear a relationship to each other; this
❖ Note View implementation varies to some degree among most RDBMS software. Make sure you examine your RDBMS’s docu-
mentation to determine how fully the RDBMS supports views and
what types of constraints it imposes (if any) on modifying the data
in a view.
Figure 12.2. Information from the EMPLOYEE PHONE LIST view.
EmpPhone NumberEmpLast Name
Erlich
McLain
Rosales
EmpFirst Name
Zachary
Susan
Joe
Employee ID
Employee Phone List
Black
Christian
Barlet
Alastair
Katie
Diana
553-3992
790-3992
551-4993
227-4992
525-2993
248-4953
100
101
102
103
104
105
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helps ensure that the information the view presents is both valid and
meaningful. For example, assume you’re designing a database for a lo-
cal community college and that the tables in Figure 12.3 are part of the
database. You’ve just decided that you need to create a view called
CLASS ROSTER that shows the name of each class and the names of
the students who are currently registered to attend it. This will be an
easy task for you to perform because you can use these three tables as
the basis of the view; they contain the fields you need to define the view,
and they bear a relationship to one another.
Now you define the CLASS ROSTER view by using the CLASS NAME field
from the CLASSES table and the STUDFIRST NAME and STUDLAST NAME
fields from the STUDENTS table. The appropriate student names will
appear for each class because CLASSES and STUDENTS are related
(and therefore connected) through the STUDENT CLASSES linking ta-
ble. Figure 12.4 shows the diagram for the CLASS ROSTER view. Note
that no changes have been made to any of the base tables.
Every time you access the CLASS ROSTER view, the RDBMS will re-
build and repopulate it using the most current data from the view’s
base tables. Figure 12.5 shows a sample of the view’s data.
Figure 12.3. Base tables for the CLASS ROSTER view.
Student Classes
Student ID
Class ID
Students
CPK/FK
CPK/FK
PK
Classes
FK
PKClass ID
Class Name
Class Description
Category
Student ID
StudFirst Name
StudLast Name
StudStreet Address
StudCity
StudState
StudZipcode
StudHome Phone
StudEmail Address
Instructor ID
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Anatomy of a View 453
Figure 12.4. The diagram for the CLASS ROSTER view.
Students Classes
Student ID
Class ID
Students
CPK/FK
CPK/FK
PK
Classes
PKClass ID Class Name Class Description
Category
Student ID StudFirst Name StudLast Name StudStreet Address StudCity StudState StudZipcode StudHome Phone StudEmail Address
FKInstructor ID
Class Roster
Class Name
StudFirst Name
StudLast Name
Figure 12.5. A partial sample of data from the CLASS ROSTER view.
Class Roster
Class Name
Advanced Music Theory
American History
Advanced Calculus
StudLast Name
Carter
StudFirst Name
Gina
ApplebeeMartin
CarterGina
RosalesJoe
UlrichSara
HernandezMike
McLainSusan
TurnerLee
McLainSusan
BarletGeorge
RosalesJoe
Advanced Calculus
Advanced Calculus
Advanced Calculus
Advanced Music Theory
Advanced Music Theory
American History
American History
American History
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You can modify most of the data within a multitable data view at any
time, and the modifications you make will flow through the view and
into the base tables. Quite obviously, you can’t modify the value of any
primary keys that you incorporate from the base tables. As in the case
of a single-table view, field specifications and business rules will deter-
mine what types of modifications you can make to the data. (Again, be
sure to check your RDBMS documentation for any further constraints it
may place upon your views.)
The redundant data in the CLASS ROSTER view (which you should
have noticed) is the result of merging a record from the CLASSES table
with two or more records from the STUDENTS table; the number of
times a particular class name appears is equal to the number of stu-
dents that are registered to attend that class. This apparent redun-
dancy is acceptable because the data is not physically stored in the
view—rather, it is drawn from the view’s base tables, where it is stored
in accordance with the rules of proper database design. RDBMSs com-
monly display data from multitable views in this fashion.
Another point to note is that a data view does not contain its own pri-
mary key. It lacks a primary key because it is not a table; a true table
stores data and requires a primary key to serve as a unique identifier for
each of its records. You can incorporate a primary key from any (or all)
of the base tables within the view, however, when you determine it will
contribute to the information the view provides.
Aggregate View
You use this type of view to display information produced by aggregat-
ing a particular set of data in a specific manner. As with a data view,
❖ Note In order to avoid any unnecessary ambiguity or confu- sion, make certain you do not have any primary key indicators
within the view symbol when you diagram a data view.
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Anatomy of a View 455
you can define an aggregate view using one or more base tables. You
can then include one or more calculated fields that incorporate the
functions that aggregate the data and one or more data fields (drawn
from the view’s base tables) to group the aggregated data. Sum, Average
(arithmetic mean), Minimum, Maximum, and Count are the most com-
mon aggregate functions that you can apply to a set of data, and every
major RDBMS supports them.
Let’s say that you wanted to know how many students are registered
for each class, and you’re using the tables from the school example
shown in Figure 12.3. Your first impulse is to define a data view called
CLASS REGISTRATION that will provide the information you need to
answer your question. So, you use the CLASS NAME field from the
CLASSES table and the STUDENT ID field from the STUDENT CLASSES
table to build the view. Figure 12.6 shows a diagram for the new CLASS
REGISTRATION view.
Figure 12.6. View diagram for the new CLASS REGISTRATION view.
Students Classes
Student ID
Class ID
CPK/FK
CPK/FK
Classes
PKClass ID Class Name Class Description
Category FKInstructor ID
Class Registration
Class Name
Student ID
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Now you access the view so that you can answer your question.
Figure 12.7 shows a partial sample of the data in the view.
In order to answer your question, you must now count each instance of
a given class name so that you can determine how many students are
registered for that class. Imagine the work you have ahead of you—this
will not be an easy task! Rather than going though all this tedious work,
you can answer your question quite easily (and more efficiently) using
an aggregate view.
There’s no need to define a new view because you can modify the one you
have just now. Remove the STUDENT ID field from the view and replace it
with a calculated field called TOTAL STUDENTS REGISTERED that counts the
number of students per class. (When you work with a calculated field,
make certain that you give it a name that is meaningful and that will dis-
tinguish it from other calculated fields in the view.) The calculated field
will use a Count function to count the number of STUDENT IDs in the
Figure 12.7. A partial sample of data from the CLASS REGISTRATION view.
Class Registration
Class Name
Advanced Music Theory
Business Administration
Advanced Calculus
Advanced Calculus
Advanced Calculus
Advanced Calculus
Advanced Music Theory
Advanced Music Theory
Business Administration
Business Administration
Business Administration
Student ID
1003
1025
1073
1110
1045
1066
1085
1025
1066
1017
1073
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STUDENT CLASSES table that are associated with each CLASS ID in
the STUDENT CLASSES table. (Later, you’ll learn how to document a
view and record the expression the calculated field will use.) Figure 12.8
shows the revised diagram for the CLASS REGISTRATION view.
As was the case with the data view, the RDBMS will rebuild and repop-
ulate the CLASS REGISTRATION view every time you access it, using
the most current data from the view’s base tables. Figure 12.9 shows a
sample of the view’s data.
There are three things to note about this view:
1. The TOTAL STUDENTS REGISTERED field displays a single number for
each class name, which represents the total number of students
registered for that class.
Figure 12.8. Revised diagram for the CLASS REGISTRATION view.
Students Classes
Student ID
Class ID
CPK/FK
CPK/FK
Classes
PKClass ID Class Name Class Description
Category FKInstructor ID
Class Registration
Class Name
Total Students Registered
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2. The redundancy within the CLASS NAME field has been eliminated;
all instances of a given class name have been grouped into a single
instance. As a result, CLASS NAME is now a grouping field, and its
values cannot be modified in any way.
3. Because an aggregate view is composed entirely of grouping fields
and calculated fields, you cannot modify any of its data.
An aggregate view is most useful as the basis of a report or as a means
of providing various types of statistical information. You’ll learn later
that you can apply filtering criteria to this (or any) view in order to con-
trol and restrict the data that the view displays.
Validation View
A validation view is similar to a validation table in that it can help im-
plement data integrity. When a business rule limits a particular field’s
❖ Note All data fields in an aggregate view are grouping fields.
Figure 12.9. A sample of data from the revised CLASS REGISTRATION view.
Class Registration
Class Name
Advanced Calculus
Total Students Registered
80
92
80
84
98
80
60
84
Advanced Music Theory
Business Administration
Introduction to Database Design
Introduction to Biology
English Literature
Pan-American Studies
Computers in Business
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Anatomy of a View 459
range of values, you can enforce the constraint just as easily with a val-
idation view as you can with a validation table. The difference between
the two lies in their construction—a validation table stores its own data,
whereas a validation view draws data from its base tables. Although you
can define a validation view using one or more base tables, you’ll com-
monly define a validation table using a single base table and incorporate
only two or three of the base table’s fields. (This structure is quite simi-
lar to that of a validation table.)
For example, let’s say you’re designing a database for a small contractor
and you’re working with the tables in Figure 12.10.
As you can see, the SUBCONTRACTOR ID field in the SUBCONTRACTORS
table provides the range of values for the SUBCONTRACTOR ID field in the
PROJECT SUBCONTRACTORS table. (Recall that a foreign key draws
its values from the primary key to which it refers.) You’ve determined,
however, that you want to restrict the access users currently have to
certain fields in the SUBCONTRACTORS table; you’ve decided that the
only fields users should be able to access are the SUBCONTRACTOR ID, SC-
NAME, SCPHONE NUMBER, and SCFAX NUMBER fields. So, you define a vali-
dation view called APPROVED SUBCONTRACTORS that will incorporate
Figure 12.10. Tables from a database for a small contractor.
Project Subcontractors
Subcontractors
CPK/FK
CPK/FK
PK
Projects
PK
FK
Project ID
Project End Date
Project Name
Project Start Date
Category ID
Subcontractor ID
Project ID
Subcontractor ID
SCName
SCStreet Address
SCCity
SCState
SCZipcode
SCPhone Number
SCFAX Number
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these fields and still provide the range of values for the SUBCONTRACTOR ID
field in the PROJECT SUBCONTRACTORS table. Figure 12.11 shows a
revised diagram of the tables, including the new view.
The APPROVED SUBCONTRACTORS view now gives users access only
to those fields that you’ve indicated and provides the appropriate range
of values for the SUBCONTRACTOR ID field in the PROJECT SUBCONTRAC-
TORS table. Additionally, the view will still enforce the relationship
characteristics that exist for the SUBCONTRACTORS table because it
(as you will recall) is the view’s base table.
Determining and Defining Views
By now you’ve probably realized that views can be a substantial asset to
the database. During this stage of the database-design process, you’ll
define a fundamental set of views for the database. Your definition of
views won’t stop here—you’ll probably define more views when you im-
plement the database within your RDBMS and as you create your end-
user application programs. In these instances, you’ll use views as a tool
to support particular aspects of the implementation or application pro-
gram. The views you define during the database-design process, how-
ever, will focus strictly on data-access and information-retrieval issues.
Figure 12.11. Revised table diagram; note the new APPROVED SUBCONTRAC- TORS view.
Approved Subcontractors
PK
Projects
PK
FK
Project ID
Project End Date
Project Name
Project Start Date
Category ID
Project Subcontractors
CPK/FK
CPK/FK
Subcontractor ID
Project ID
Subcontractor ID
SCName
SCPhone Number
SCFAX Number
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Working with Users and Management
You’ll work once again with the organization’s representative group of
users and management to identify the types of views the organization
requires. After you identify these views, you’ll establish and document
them, and then you and the group will review the views to make certain
that they are properly defined.
Before you conduct your first meeting with the group, review the notes
you’ve taken throughout the entire design process. Your objective is to get
an idea of the types of views the organization might need. Almost every
organization spends a large amount of time producing and reading re-
ports, so you should focus on that aspect of your notes. You should also
review the report samples you assembled during the analysis process.
When you and the group meet, consider the following points to help you
identify view requirements:
• Review your notes with the group. In many instances, talking
about a specific topic will spark an idea for a new or required
view. For example, someone may realize a need for a view during a
discussion of mission objectives.
• Review the data-entry, report, and presentation samples you gath-
ered during the early stages of the design process. Examining
these samples, especially summary-style reports, could easily il-
luminate the need for certain types of views.
• Examine the tables and the subjects they represent. Some individu-
als in the group may identify the need for a view based solely on a
specific subject. If someone mentions a subject, such as Employ-
ees, it may cause someone else to say, “We definitely need a view
that restricts certain employee data for confidentiality reasons.”
• Analyze the table relationships. You’ll most likely identify a num-
ber of multitable views that you should create for many of the
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relationships. Several of these views will coincide with views you
identified for the report samples.
• Study the business rules. As you already know, you can use a val-
idation view to enforce a rule that imposes a constraint on a
particular field’s range of values.
You and the group should be able to identify a number of views by going
over the items on this list. After you’ve identified as many of the re-
quired views as possible, your next task is to define them.
Defining Views
You’ll now define each view that you’ve identified using the appropriate
tables and fields. Review the relationship diagrams to identify which ta-
bles and fields you need for the view’s structure. When you’ve deter-
mined what you need, define the view and record it in a view diagram.
For example, say you’ve determined that you can use a view for the re-
port shown in Figure 12.12; the name of the new view will be CUS-
TOMER CALL LIST.
The notes you’ve taken throughout the design process become useful
once again. You reviewed this report during the analysis stage of the de-
sign process, and you’ve noted that this report represents information
about customers and their orders; it is from the order data that you can
determine when a given customer made his last purchase. Now, review
the relationship diagram for the CUSTOMERS and ORDERS tables;
you’ll use fields from these tables to create the CUSTOMER CALL LIST
view. Figure 12.13 shows the relationship diagram for these tables.
After examining the relationship diagram, you determine you need to
use five fields to build this view: CUSTFIRST NAME, CUSTLAST NAME, CUST-
PHONE NUMBER, and CUSTCITY from the CUSTOMERS table, and ORDER
DATE from the ORDERS table. You now define the CUSTOMER CALL
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Determining and Defining Views 463
Figure 12.12. Report sample requiring a view.
Bothell Sara Anderson 542-0039 05/16/02
City Customer Name Phone Number Last Purchase
Jim Booth 367-4495 02/11/02
Larry Currey 445-3394 02/06/02
Bellevue Jim Davis 545-9932 05/10/02
Larry Lang 545-3384 01/22/02
Sandra Wasser 367-2293 06/30/02
Edmonds Julia Black 223-9943 04/12/02
Lynnwood Mary McLain 562-1274 02/28/02
Barbara Reeves 445-2094 03/07/02
Customer Call List
Figure 12.13. Relationship diagram for the CUSTOMERS and ORDERS tables.
Orders
PKOrder Number
Employee ID FK
Customer ID FK(R) PK
Customers
Customer ID
CustFirst Name
CustLast Name
CustStreet Address
CustState
CustZipcode
CustPhone Number
Status
CustCIty
Ship Date
(1,1)
(0,N)
Order Date
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LIST view by assigning the fields to the view and then recording them in
a view diagram. When you’re finished, your diagram should look like the
one in Figure 12.14.
Using Calculated Fields Where Appropriate
Earlier in the database-design process, you learned that tables couldn’t
contain calculated fields for a number of good reasons. But one of the
characteristics of a view that makes it so useful is that it can contain
calculated fields. Recall that calculated fields will display the result of a
Figure 12.14. View diagram for the CUSTOMER CALL LIST view.
Orders
(R) PK
Customers
Customer ID
CustFirst Name
CustLast Name
CustStreet Address
CustState
CustZipcode
CustPhone Number
Status
CustCIty
(1,1)
(0,N)
Customer Call LIst
CustFirst Name
CustLast Name
CustCity
CustPhone Number
Order Date
PKOrder Number
Employee ID FK
Customer ID FK
Ship Date
Order Date
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Determining and Defining Views 465
concatenation, expression, or aggregate function; this makes them an
extremely flexible structure to include in a view.
For example, consider the new CUSTOMER CALL LIST view. Although
you have the fields you need for the view, you’ll have to make one minor
modification to the view so that it can display the appropriate data. One
of the requirements for this view is that it must display the date of the
last purchase made by each customer. In order to retrieve and display
the proper date, you’ll have to add a calculated field to the view. This
field will use the Maximum function [commonly known as Max()] to re-
trieve the correct date from the ORDER DATE field. Name the new field LAST
PURCHASE DATE and add it to the CUSTOMER CALL LIST view diagram.
(You no longer need the ORDER DATE field in the view, so you can remove
it from the view’s structure.) This is the expression you’ll use in the cal-
culated field to retrieve the appropriate date:
Max(Order Date)
Later in this section, you’ll learn where and how to record this expression.
Another calculated field you might include in this view is one that dis-
plays the complete customer name by concatenating CUSTFIRST NAME and
CUSTLAST NAME. Say, for example, that you want to display the customer
name in this manner: “Hernandez, Michael.” Create a calculated field
called CUSTOMER NAME and use the following concatenation expression:
CustLast Name & “, “ & CustFirst Name
Add the new calculated field to the CUSTOMER CALL LIST view diagram
and remove the CUSTFIRST NAME and CUSTLAST NAME fields from the view;
❖ Note Be sure to refer to your RDMBS’s documentation to de- termine the correct syntax for this function and all of the other
functions used in this chapter.
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you don’t need these fields anymore because you’re now using the CUS-
TOMER NAME calculated field. (You’ll soon properly record this expression
as well.)
Figure 12.15 shows how your revised view diagram should look after
you’ve completed these modifications.
As you’ve just learned, calculated fields can be quite an asset because
you can use them to enhance the information a view provides. You also
learned earlier in this chapter that calculated fields are particularly cru-
Figure 12.15. Revised view diagram for the CUSTOMER CALL LIST.
Orders
(R) PK
Customers
Customer ID
CustFirst Name
CustLast Name
CustStreet Address
CustState
CustZipcode
CustPhone Number
Status
CustCity
(1,1)
(0,N)
Customer Call LIst
CustCity
Customer Phone Number
PKOrder Number
Employee ID FK
Customer ID FK
Ship Date
Order Date
Customer Name
Last Purchase Date
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Determining and Defining Views 467
cial in aggregate views. A good rule of thumb to follow when you think
you may need calculated fields is to use them if they will provide perti-
nent and meaningful information or if they will enhance the manner in
which the view uses its data.
If you recall, you created a calculated-field list earlier in the design pro-
cess (refer to Chapter 6). You can now use this list as a source of calcu-
lated fields that you might (or should) use in your views. Review the list
as you define each new view and determine whether you can use one of
the calculated fields on the list. When you find one that you can use,
create it in the same manner as you did in the preceding examples. (If
you create a new calculated field that does not appear on your list, how-
ever, be sure to add it to the list. This will help you keep your calcu-
lated-field list current and in order.)
Imposing Criteria to Filter the Data
Views have another characteristic that makes them extremely useful:
You can impose criteria against one or more fields in the view to filter the
records it displays. For example, say that the CUSTOMER CALL LIST
view included the CUSTSTATE field. Although the view would continue to
display the set of records it did before, you would also see the state in
which each customer lives. Assume, however, that you want the view to
show a particular set of records, such as those for customers who live in
the state of Washington. You can accomplish this by setting a specific
criterion on the CUSTSTATE field that will filter the data so that the view
displays only those records of customers from Washington State.
❖ Note In database work, the word “criterion” refers to an ex- pression that is tested against the value of a particular field. The
view will include a given record if the value of the field meets the
criterion.
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This is the expression you will use to filter the records for the CUS-
TOMER CALL LIST view:
CustState = “WA”
Now the view will display only customers from Washington. If you want
to filter the records further to show only those customers who live in
specific cities, you add a criterion such as this:
CustCity In (“Bellevue,” “Olympia,” “Redmond,” “Seattle,”
“Spokane,” “Tacoma”)
The view will now display Washington State customers who live in the
cities specified in the expression. You may wonder why both criteria are
necessary—the criterion for the CUSTCITY field should retrieve the appro-
priate records by itself. The trouble is that many cities are named for
other cities, so that cities in two or three different states could have the
same name. For example, there is a Portland, Oregon, and a Portland,
Maine, both named after Portland, England. The point to remember is
that you must use your best judgment when you establish criteria for a
view—use the minimum number of criteria that will cause the view to
display the records you require.
When you use a criterion in a view, you must make certain that the field
you’re testing in the criterion is included in the view’s structure. If you
do not include the field in the view, you have no way of imposing the cri-
terion. This is an important point to remember because it is a require-
ment when you logically define a view and when you implement the view
in your RDBMS.
The one problem with applying a filter to a view is that there is no way
to indicate it on a view diagram; therefore, you must record it on a View
Specifications sheet.
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Determining and Defining Views 469
Using a View Specifications Sheet to Record the View
A View Specifications sheet must accompany each view diagram you
create. It is on this sheet that you will record the characteristics of the
view. The View Specifications sheet contains the following items:
• Name. This is where you indicate the name of the view. Before you
record the name, however, test it against the guidelines for creat-
ing table names you learned in Chapter 7. These guidelines gov-
ern the naming of views as well, with one exception: The name of
a view can implicitly or explicitly identify more than one subject.
This is because you can define views from two or more base ta-
bles, so they do, indeed, represent more than one subject.
• Type. This is where you indicate whether you’re defining a data,
aggregate, or validation view.
• Base tables. This is where you specify the names of the view’s base
tables. Although the view diagram shows these tables, they appear
here as a matter of convenience. The View Specifications sheet
does not include field names, however, because you can record
and display them more easily and efficiently on the view diagram.
• Calculated-field expressions. This is where you record the expres-
sions for the calculated fields you included in the view. As you
record the name of the calculated field, test it against the guide-
lines for creating field names you learned in Chapter 7. Calcu-
lated field names are governed by these guidelines with two
exceptions: You can implicitly or explicitly identify more than one
characteristic in a name, and you can use the plural form of the
name. But it’s still desirable to use the singular form of the name
whenever possible.
• Filters. This is where you record the criteria that the view will use
to filter the records it displays. You’ll record both the field being
tested and the expression used to test it.
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Fill out a View Specifications sheet for each view you create and attach
the sheet to the proper view diagram. Both of these items will serve to
document the view fully. Figure 12.16 shows a completed View Specifi-
cations sheet for the CUSTOMER CALL LIST view. (Keep in mind that
the view has been updated to include the CUSTSTATE field.)
Reviewing the Documentation for Each View
Once you’ve completed the task of defining and documenting each view,
review all of your views once more—ensuring that the quality of the in-
formation each view provides is well worth the effort. As you review each
view, keep the following points in mind:
• Make certain that you’ve defined the view properly. Think about
the information the view should provide. Are you establishing the
correct type of view for the required information? Did you use the
appropriate base tables to define the view? Did you include all
the necessary fields within the view’s structure?
• Make certain that the calculated fields you’ve created are suitable
for the view. Do they provide pertinent and meaningful informa-
tion? Do they serve to enhance the manner in which the view dis-
plays its data?
• Make certain that the filters will retrieve the required records. First
of all, do you need a filter for this view? If the answer is yes, do
you know exactly which records you want the view to display? Do
you believe that the filter will work correctly?
• Above all, make certain that you have a view diagram and View
Specifications sheet for each view. This documentation will be very
useful when you finally implement the database in an RDBMS.
❖ Note When you fill out the Calculated-Field Expressions and Filters sections of a View Specifications sheet, use the expres-
sions with which you are most familiar. You’ll modify them as
necessary when you implement the database in an RDBMS.
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Determining and Defining Views 471
Figure 12.16. Completed View Specifications sheet for the CUSTOMER CALL LIST view.
Description:
Field Name
VIEW SPECIFICATIONS
Base Tables
General Information
Calculated Field Expressions
Filters
Field Name Condition
Expression
This view provides information that allows us to execute follow-up calls to our customers in Washington. Also indicated is the date of the customer's last purchase.
CUSTOMERS, ORDERS
CUST STATE
CUST CITY
CUSTOMER NAME
LAST PURCHASE DATE Max(ORDER DATE )
="WA"
In ("Bellevue", "Olympia", "Redmond", "Seattle", "Spokane", "Tacoma")
CUST LAST NAME & ", " & CUST FIRST NAME
Customer Call ListName: Type: Data ValidationX Aggregate
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472 Chapter 12 Views
Your work on Mike’s database is finally nearing an end. You meet with
Mike and his staff to determine whether there is a need to establish
views for the database. The agenda you’ve set up for the meeting in-
volves the following steps:
1. Review the notes you’ve compiled during the design process.
2. Review each of the various samples you gathered during the early
stages of the design process.
3. Examine the subjects represented by the tables in the database.
4. Analyze the table relationships.
5. Review and study the business rules.
As the meeting progresses, you identify several views that you need to
define, including a PREFERRED CUSTOMERS view and a VENDOR
PRODUCT COUNT view. The first view will provide the name and phone
number of each customer who has a “Preferred” status, and the second
view will provide information on the total number of different products
each vendor supplies.
You base the PREFERRED CUSTOMERS view on the CUSTOMERS ta-
ble and use the CUSTOMERID, CUSTFIRST NAME, CUSTLAST NAME, CUSTHOME
PHONE, and STATUS fields for the view’s structure. Before you construct
the view, however, Mike asks if there’s any way to display the first name
and last name together. You respond that it can be done, so you create a
calculated field called CUSTOMER NAME that concatenates both of the
fields together; this field will now replace the CUSTFIRST NAME and CUST-
LAST NAME fields. Figure 12.17 shows the view diagram for the PRE-
FERRED CUSTOMERS view.
CASE STUDY
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Case Study 473
After you create the view diagram, you make note of the expression that
you’ll use to filter the view’s data:
Status = “Preferred.”
Then you complete a View Specifications sheet for the PREFERRED
CUSTOMERS view. Figure 12.18 shows the results of your work.
Now you define the VENDOR PRODUCT COUNT view using the VENDORS
and PRODUCTS tables as the view’s base tables. You use the VENDOR
NAME field from the VENDORS table to display the names of the vendors.
Figure 12.17. View diagram for the PREFERRED CUSTOMERS view.
Customer ID
CustFirst Name
CustLast Name
CustStreet Address
CustCity
CustState
CustZipcode
CustPhone Number
Status
Customers
PK
Customer Name
CustHome Phone
Status
Customer ID
Preferred Customers
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Figure 12.18. The View Specifications sheet for the PREFERRED CUSTOMERS view.
Description:
Field Name
Field Name Condition
Expression
Name: Type: Data ValidationX Aggregate
This View provides the names and phone numbers of our Preferred customers. We use this information in support of the services we provide to these customers.
CUSTOMERS
CUSTFIRST NAME & “ ” & CUSTLAST NAME
Preferred Customers
STATUS
CUSTOMER NAME
=“Preferred”
VIEW SPECIFICATIONS
Base Tables
General Information
Calculated Field Expressions
Filters
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Case Study 475
Next, you create a calculated field called PRODUCT COUNT to display the
total number of products each vendor supplies. This is the expression
the field uses to calculate the total:
Count(ProdName)
Now you create a diagram for the view, as shown in Figure 12.19.
After determining that a filter is unnecessary for this view, you finish
documenting the view by completing the View Specifications sheet
shown in Figure 12.20.
You then repeat this process for every view you’ve identified for Mike’s
database.
Figure 12.19. View diagram for the VENDOR PRODUCT COUNT view.
(R) PK
(1,1)
(0,N)
Vendor Product Count
Product Count
Vendor Name
Products
Product Number
ProdDescription
ProdName
Category
Retail Price
Wholesale Price
Vendor ID
Vendors
Vendor ID
VendName
VendFax Number
VendStreet Address
VendCity
State
VendZipcode
VendPhone Number
FK
PK
FK
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Figure 12.20. View Specifications sheet for the VENDOR PRODUCT COUNT view.
Description:
Field Name
Field Name Condition
Expression
Name: Type: Data ValidationAggregate
This view tells us how many products are supplied by each vendor. This information will help us determine which vendors we might need to drop.
VENDORS, PRODUCTS
Count(PRODNAME)
Vendor Product Count
PRODUCT COUNT
X
VIEW SPECIFICATIONS
Base Tables
General Information
Calculated Field Expressions
Filters
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Summary 477
Summary
We began this chapter with a definition of a view, and you learned that
it is a virtual table that does not contain or store data. Views are useful
for several reasons—they provide a means for you to work with data
from multiple tables, they help enforce data integrity, and they help
keep data secure or confidential.
We then discussed the three types of views: data, aggregate, and valida-
tion. You learned that each type of view can be based on one or more ta-
bles, other views, or a combination of both. Your RDBMS will rebuild
and repopulate a view every time you access it, using the most current
data from the view’s base tables. As you now know, there must be rela-
tionships between tables in a multitable view (thus making the view’s
information valid and meaningful), and the characteristics of those rela-
tionships are carried forth through the view. Additionally, you can mod-
ify most views, and all the modifications you make to the data are
passed through the view to the base tables. You also learned that vali-
dation views work in the same manner as validation tables and that
they have distinct advantages over validation tables. For instance, vali-
dation views can incorporate data from multiple tables.
The chapter then continued with a discussion of determining and defin-
ing views for the database. Here you learned several specific points to
keep in mind while you work with users and management to identify the
organization’s view requirements. Next, we discussed how to define a
view, and you learned how to create a view diagram to document the
view. Now you know how to select fields from the base tables and assign
them to the view.
We then discussed how to use calculated fields in a view. You learned
that you could use them to help provide pertinent information and to
enhance how the view displays its data. You also learned that calculated
fields are especially crucial in aggregate views and that each calculated
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478 Chapter 12 Views
field uses an expression to derive the value it displays. Next, you learned
how to apply a filter to a view so that it will retrieve and display a spe-
cific set of records. The view will display a given record only if it meets
the criteria you’ve imposed against one or more fields in the view. You
frame each criterion as an expression and use it to test the value of a
particular field.
The chapter closed with a discussion of the View Specifications sheet.
Here you learned how to document the characteristics of the view, such
as its name and type. You also learned about the items that compose
the View Specifications sheet and how you use them to record the view’s
characteristics.
Review Questions
1. Why can you refer to a view as a virtual table?
2. State two reasons why views are valuable.
3. Name the types of views you can define as you design the logical
structure of the database.
4. What does your RDMBS do each time you access a data view (or
any type of view, for that matter)?
5. What determines the type of modifications you can make to a
view’s data?
6. What is the only requirement you must fulfill in order to define a
multitable data view?
7. Why doesn’t a data view contain its own primary key?
8. What is the purpose of an aggregate view?
9. What are the most common aggregate functions that you can apply
to a set of data?
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Review Questions 479
10. What is a grouping field?
11. True or False: You can modify the data in an aggregate view.
12. What is the difference between a validation table and a validation
view?
13. Name two points you would consider when identifying view
requirements.
14. When should you use calculated fields?
15. How do you define a view that displays only science-fiction books?
16. Why must you complete a View Specifications sheet for every view
in the database?
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13 Reviewing Data Integrity
When you have eliminated the impossible, whatever remains, however improbable, must be the truth.
—SHERLOCK HOLMES, THE SIGN OF FOUR
Topics Covered in This Chapter
Why You Should Review Data Integrity
Reviewing and Refining Data Integrity
Assembling the Database Documentation
Done at Last!
Case Study—Wrap Up
Summary
You are now at the final stage of the database-design process. You’ve ac-
complished many things since you started the process. Thus far you
have
• Perceived the advantages of the relational database model and
how it compares to other database models
• Created a mission statement for a new database
• Defined mission objectives for the new database
• Performed a complete analysis of an old database
• Identified the organization’s information requirements
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• Defined all the appropriate table structures
• Assigned a primary key to each table
• Established field specifications for each field
• Established table relationships
• Defined and established business rules
• Defined all the appropriate views
• Established overall data integrity
For all intents and purposes, your new database is complete; neverthe-
less, it would be to your advantage to perform one final review of the
overall data integrity of your database.
Why You Should Review Data Integrity
You’re probably wondering why you should review the database struc-
ture one last time, given that you’ve paid attention to every detail and
have focused on data integrity throughout the entire design process.
The answer is simple: You want to make certain that the data integrity
you’ve been so careful to establish is absolutely as sound as possible.
As you well know, a crack in the integrity could result in inconsistent
data or inaccurate information. However improbable, it is possible that
you may have overlooked something. The peace of mind you gain from
knowing that you have a solidly designed database is well worth the
time and effort of this final review.
❖ Note Remember: Garbage in, garbage out!
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Reviewing and Refining Data Integrity 483
Reviewing and Refining Data Integrity
Reviewing data integrity is a simple task if you take a modular ap-
proach, that is, if you sequentially review each component of overall
data integrity: table-level, field-level, and relationship-level integrity and
business rules. If you have carefully followed the design method pre-
sented in this book, you should encounter very few problems here. The
following sections briefly outline the points you should keep in mind as
you conduct the review, and they contain references to earlier chapters
in case you encounter any problems.
At the Table Level
In order to ensure that you’ve properly established table-level integrity,
review each table and make certain that the table conforms to all of the
following points:
• There are no duplicate fields in the table.
• There are no calculated fields in the table.
• There are no multivalued fields in the table.
• There are no multipart fields in the table.
• There are no duplicate records in the table.
• Every record in the table is identified by a primary key value.
• Each primary key conforms to the Elements of a Primary Key.
If you believe you have problems with any of these items, resolve them
using the techniques and concepts discussed in Chapters 6 through 8.
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At the Field Level
You can ensure that you’ve properly established field-level integrity after
you’ve done the following:
• Made sure each field conforms to the Elements of the Ideal Field
• Made certain you’ve defined a set of field specifications for each
field
You can resolve field-level integrity problems with the techniques dis-
cussed in Chapter 9.
At the Relationship Level
Examine each table relationship to ensure that you’ve properly estab-
lished relationship-level integrity. You’ve achieved this level of integrity
when you’ve completed these tasks:
• Properly established the relationship
• Defined the appropriate deletion rules
• Correctly identified the type of participation for each table
• Established the proper degree of participation for each table
If you identify a problem with a relationship, use the techniques in
Chapter 10 to resolve it.
At the Level of Business Rules
You can ensure that your business rules are sound by making certain
these tasks are complete:
• You’re sure that each rule imposes a meaningful constraint.
• You’ve determined the proper category for the rule.
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Reviewing and Refining Data Integrity 485
• You’ve properly defined and established each rule.
• You’ve modified the appropriate field specification elements or
table-relationship characteristics.
• You’ve established the appropriate validation tables.
• You’ve completed a Business Rule Specifications sheet for each
rule.
If you encounter problems with any of your business rules, refer to
Chapter 11 for the techniques necessary to solve them.
At the Level of Views
Although views are not directly connected to any component of data in-
tegrity, you should nevertheless review all of your view structures. As
you examine each view, make certain you’ve addressed these items:
• Each view contains the base tables necessary to provide the re-
quired information.
• You’ve assigned the appropriate fields to each view.
• Each calculated field provides pertinent information or enhances
the manner in which the view presents its data.
• Each filter returns the appropriate set of records.
• Each view has a view diagram.
• Each view diagram is accompanied by a View Specifications sheet.
If you encounter problems with any view, resolve them by using the
techniques discussed in Chapter 12.
Once you’ve completed this entire review, you can be confident that the
database structure is sound, the data within the database is consistent
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and valid, and the information you retrieve from the database will be
accurate.
Assembling the Database Documentation
Throughout the database-design process, you’ve generated a number of
lists, specification sheets, and diagrams used to record various aspects
of the database-design. You should now assemble them into a central
repository, preferably in a set of binders. (Incidentally, you could gener-
ate and store these documents using a computer program.) The design
repository should consist of the following sets of documents:
Two additional sets of items you may consider keeping with this docu-
mentation are the notes you compiled during the design process and
the samples you gathered during the analysis stage of the design pro-
cess. You can keep each of these items in a separate appendix at the
end of the documentation.
All of these items constitute the complete set of documentation for the
logical design of the database. This documentation is vital for three
reasons:
1. It provides a complete record of the database structure. You can find
every aspect of the logical structure of the database within the doc-
umentation. Additionally, you can answer almost any question
concerning the database simply by referring to the documentation.
2. It provides a complete set of specifications and instructions on how
the database should be created during the implementation process.
Final table list
Field Specifications sheets
Calculated-field list
Table structure diagrams
Relationship diagrams
Business Rule Specifications sheets
View diagrams
View Specifications sheets
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Case Study—Wrap Up 487
This documentation is similar to an architect’s blueprints: It indi-
cates how the database is to be constructed. It also identifies the
integrity that needs to be established for the database. Because
the database design is not directed to a particular RDBMS, the
individuals implementing the database have full latitude concern-
ing the manner in which they physically implement the database.
3. Should it seem necessary to modify the database structure during
the implementation process, the design documentation can be used
to determine the effects and consequences of any modifications. Any
modifications you make to the database structure should be the
result of an informed decision. You can make certain that a pro-
posed modification will not have an adverse effect on the database
structure by referencing the documentation first.
Done at Last!
Now that you’ve completed the integrity review and assembled all of the
documentation for the database, the logical database-design process is
complete. You can rest assured that you have a properly designed data-
base and that its implementation will proceed smoothly. On to the next
client and the next database design!
This is your last meeting with Mike and his staff. Your objective is to re-
view his database and its integrity one final time. Although you’re confi-
dent that you will not find any problems, you want to give the database
one final quality-control review.
During the meeting, you review each of the database structures to en-
sure that they are in accordance with the various elements that govern
CASE STUDY—WRAP UP
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them. Then you review each component of overall data integrity to make
certain that you’ve properly established table-level, field-level, and rela-
tionship-level integrity, as well as business rules. Finally you gather all
of the documentation you’ve generated throughout the design process.
After you’ve assembled all of the documentation into a set of binders,
you give them to Mike and declare that his database is now complete.
Mike expresses his thanks and gratitude for a job well done and prom-
ises your check will be in the mail by the 15th of the month. You ex-
press your thanks to Mike and his staff, say your good-byes and depart
for new horizons. As you leave, Mike stares in your direction; one final
thought occurs to him.
“Now, if I could just get you to implement my database for me . . .”
Summary
The chapter opened with a list of your accomplishments since you be-
gan the database-design process. It then continued with a discussion of
why you should review overall data integrity one final time. This was fol-
lowed by a brief discussion of the points to keep in mind as you review
each component of overall data integrity. We close the chapter by dis-
cussing the importance of the documentation you’ve assembled during
the entire design process.
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Part III Other Database- Design Issues
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14 Bad Design—What Not to Do
Mistakes are always initial. —CESARE PAVESE
Topics Covered in This Chapter
Flat-File Design
Spreadsheet Design
Database Design Based on the Database Software
A Final Thought
Summary
You may have wondered why this chapter appears at the end of the
book instead of at the beginning. The reason is simple: You can appreci-
ate the dangers presented by a poorly designed database now that
you’ve learned how to design a database properly. Additionally, you will
be able to determine for yourself why a particular design is bad—you’ll
look at the design and be able to identify the problems with the struc-
ture immediately. You also possess the knowledge required to identify
possible solutions to these problems.
In this chapter, you’ll see the three most common design approaches
that lead to poorly structured databases. The discussions are brief be-
cause they are only meant to illustrate types of design you should
avoid. It should now be obvious that the way to resolve an improperly
designed database is to take it through the complete design process
you’ve just learned.
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Flat-File Design
This type of design (sometimes known as the “throw-everything-into-
one-big-table” design) has been in existence for many years and is com-
mon in databases that have been designed for implementation in nonre-
lational database-management systems. A flat-file design is fraught with
problems, as you can see by examining the structure in Figure 14.1.
This diagram represents the structure of a single table. (Imagine how
other tables within the database are structured!) You can readily see
that this structure will inevitably cause problems with redundant data
and inconsistent data and that it suffers from a lack of data integrity.
As you’ve probably already noted, there are a few other problems with
this structure:
Figure 14.1. An example of a flat-file structure.
Customer Orders
Table Structures
Customer Number Item 2
Customer Name Quantity 2
Customer Address Price 2
Order Number Customer Phone Item 2 Extension
Order Date Item 1 Item 3
Ship Date Quantity 1 Quantity 3
Order Amount Price 1 Price 3
Sales Rep Name Item 1 Extension Item 3 Extension
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• Multipart fields. SALES REP NAME includes the sales rep’s first and
last name, CUSTOMER NAME includes the customer’s first and last
name, and CUSTOMER ADDRESS includes the customer’s street ad-
dress, city, state, and zip code.
• Calculated fields. The ORDER AMOUNT field contains a value that is
most likely manually calculated, especially if the customer is or-
dering more than three items. The ITEM # EXTENSION fields are all
likely to be manually calculated as well. The value for a given ITEM
# EXTENSION field is the result of multiplying the value of a related
QUANTITY # field by the value of a related PRICE # field. (For exam-
ple: ITEM 3 EXTENSION = QUANTITY 3 × PRICE 3)
• Unnecessary duplicate fields. Each of the fields pertaining to a
particular item is a duplicate. For example, the ITEM 1, ITEM 2, and
ITEM 3 fields are unnecessary duplicate fields.
• No true primary key. There is no field or group of fields that can
uniquely identify a single record in this table. The ORDER NUMBER
field is not a primary key in this table; if a customer orders more
than three items, you’ll have to enter another record into the table
using the same order number.
• The table represents more than one subject. This table represents
three subjects: customers, orders, and items. (Depending on your
point of view, it also represents sales reps.)
Now that you know the elements of good database design, you’re sure to
avoid a design such as this.
Spreadsheet Design
A spreadsheet is certainly a good tool if you use it properly and for the
purpose for which it was designed. For example, it is quite suitable for
work that involves complex mathematical calculations and statistical
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analysis. Contrary to popular myth, however, a spreadsheet does not
make a good relational database. If your organization has a need to col-
lect, store, maintain, and manipulate various types of data, then use
the proper tool for the job by designing and implementing a real data-
base. For example, consider the spreadsheet in Figure 14.2.
This spreadsheet is being used to keep track of store managers for a
small chain of retail stores. As you can see, this approach has problems
as well.
• Duplicate fields. Each field on this spreadsheet is a duplicate field.
If you take the fields at face value, there are basically three fields
in each instance: STORE NUMBER, MANAGER NAME, and ASSISTANT MAN-
AGER NAME.
• Multipart fields. Each field holds two values. The first field stores
the store number and phone number, the second field stores the
Figure 14.2. An example of a typical spreadsheet “database.”
B C
Store 103 (554-2993)
Manager: Katie Christian
Asst. Mgr: Terri Sharpe
Store 104 (773-1837)
Manager: Gary Holcomb
Asst. Mgr: Barbara Cooper
and Tim Ennis
Store 105 (344-2883)
Manager: Caroline Coie
Asst. Mgr: LeRoy Bonnicksen
A
Store 100 (344-0029)
Manager: Mike Hernandez
Asst. Mgr: Bob McNeal and
1
2
3
Suzi Thompson4
Store 101 (433-4872)5
6
7
8
9
10
11
Manager: Abe Hernandez
Asst. Mgr: Steve McMahn
Store 102 (433-4872)
Manager: Susan McLain
Asst. Mgr: Diana Barlet
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manager’s first and last name, and the third field stores the assis-
tant manager’s first and last name.
• Multivalued fields. The ASSISTANT MANAGER field is a multivalued
field because there can be more than one assistant manager as-
signed to a particular store.
• This type of database is difficult to use. Data-oriented tasks that
can be performed with ease in an RDBMS program are tedious
and time-consuming to carry out in a spreadsheet. For example,
it would take you some time to create a list containing only the
name of each store manager and his or her phone number.
After seeing the problems associated with a simple spreadsheet “data-
base” such as this one, you can imagine the types of problems you
would encounter with a more complex database. If you’re currently us-
ing a spreadsheet as a database, you can improve the database’s qual-
ity, speed, and versatility if you remove it from the spreadsheet, take it
through the entire database-design process, and implement it in a suit-
able RDBMS.
Dealing with the Spreadsheet View Mind-set
When you begin to work with a true database and RDBMS, you must
break away from a spreadsheet view mind-set. This means that you’ll
have to resign yourself to the fact that certain ways of viewing the data
are now unavailable—you can no longer use typical spreadsheet layouts.
For example, consider a typical spreadsheet report shown in Figure 14.3.
You cannot produce a report with this type of layout using a database.
Whereas a spreadsheet stores the data exactly as you see it on the re-
port, a database would store it in four separate fields within a table. Fig-
ure 14.4 shows an example of a database report you could generate for
the same data. The database presentation is not the same as the
spreadsheet presentation, but it is just as clear.
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Figure 14.3. An example of a typical spreadsheet report.
Branch Stores
Bellevue
Store 118 Store 201 Store 211 Manager: Katherine Ehrlich Manager: Kevin Christian Manager: George Chavez
Redmond
Store 27 Store 75 Store 322 Manager: Mark Rosales Manager: Chris Weber Manager: Steve Pundt
Seattle
Store 105 Store 187 Store 200 Manager: Caroline Cole Manager: Julia Black Manager: Sanjay Jacob
Figure 14.4. An example of a typical database report.
Branch Stores
Bellevue
Store 118 Manager: Katherine Ehrlich Store 201 Manager: Kevin Christian Store 211 Manager: George Chavez
Redmond
Store 27 Manager: Mark Rosales Store 75 Manager: Chris Weber Store 322 Manager: Steve Pundt
Seattle
Store 105 Manager: Caroline Cole Store 187 Manager: Julia Black Store 200 Manager: Sanjay Jacob
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Database Design Based on the Database Software 497
The point to remember is that you’ll have to adjust the manner in which
you think about working with the data in your database. In the end,
there are far more advantages to storing and using your data in an ac-
tual database than trying to use a spreadsheet in a similar manner. A
database gives you much more control over data integrity and the con-
sistency and validity of the data. It also provides an almost unlimited
number of ways to retrieve the data, enabling you to obtain a wide vari-
ety of information.
Database Design Based on the Database Software
An RDBMS does not provide a basis or procedure or even a reason for
designing a database in a particular fashion—it only provides the tools
that you need to implement a design. In contrast, a formal database-
design method provides both the principles and rationale necessary to
define a database properly and effectively.
Many people unwittingly fall into the trap of designing a database based
solely on the RDBMS software they will use for its implementation. In
many cases, they do so because they are already somewhat familiar and
skilled with a particular RDBMS. This is an unwise approach that you
should avoid for several reasons:
• You’re likely to make design decisions based on your perceptions of
what your RDBMS can or can’t do. For example, you may decide
not to impose a degree of participation for a given relationship be-
cause you believe the RDBMS does not provide you with the
means to do so.
• You’ll inadvertently let the RDBMS dictate the design of the data-
base as opposed to driving the design strictly from the organiza-
tion’s information requirements. This usually occurs when you
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discover that your RDBMS provides only limited support for cer-
tain aspects of the database, such as field specifications and rela-
tionship characteristics.
• Your design will be constrained by your knowledge of the RDBMS.
For example, you may decide not to implement relationship char-
acteristics simply because you don’t know how to do so.
• Your design will be constrained by how skilled you are with your
RDBMS. Your skill level affects how efficiently and effectively you
can implement various aspects of the database, such as field
specifications and business rules.
• Using this approach to design a database commonly results in im-
proper structural design, insufficient data integrity, and problems
with inconsistent data and inaccurate information. Defining a da-
tabase within an RDBMS can be deceptively easy. You may create
a database that works, but you’re very likely to have a poor design
without knowing it.
• In the end, the RDBMS that you know and love so well may not be
suitable for your organization’s database requirements.
You should always design the logical structure of your database without
regard to any RDBMS. By doing so, you’re more likely to design a sound
structure because you’ll be focused on the organization’s information
requirements. Once your design is complete, you can then clearly deter-
mine how you should implement the database (single-user application,
client/server, Web-based, and so on) and which RDBMS you should use
to facilitate the implementation.
A Final Thought
Through years of teaching database design and instructing people in
how to use various RDBMS software programs, I’ve observed an inter-
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Summary 499
esting phenomenon: People who are familiar with the fundamental prin-
ciples of proper database design have a better comprehension of their
RDBMS and the tools it provides than those who know little at all about
database design. I believe this is due to the fact that the people who
know database design are able to understand why the RDBMS provides
certain tools and how they can (and should) use them. For this reason—
as well as the many others presented in this book—it is to your distinct
advantage to learn and understand good database-design techniques.
This book does not map the only road, but it is, I believe, the straight-
est, surest, and most easily traveled.
Summary
This chapter contrasted relational database design with weaker, less ef-
fective design formats. First, we looked at flat-file design. You learned
that there are numerous fatal problems with this approach and that it
should be completely avoided. We then examined spreadsheet design
and you saw how constrained this approach can be. The chapter closed
with a discussion of designing a database using RDBMS software. You
learned that this type of design is perilously dependent on your famil-
iarity and skill level with the software. Unlike a good database-design
method, designing a database around an RDBMS does not provide you
with principles and a rationale for designing a proper database struc-
ture. Superficially, in the short run, the software product looks as
good—it just doesn’t work as well in the long run as the design method
discussed in this book.
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15 Bending or Breaking the Rules
Nature never breaks her own laws. —LEONARDO DA VINCI
Topics Covered in This Chapter
When May You Bend or Break the Rules?
Documenting Your Actions
Summary
I always advocate following proper database-design techniques. As
you’ve already learned, there are numerous reasons for doing so. But
first and foremost, you should use a good design method to ensure the
integrity of the database. I cannot overstate how important this is. You
now know the consequences of improperly establishing data integrity,
so following the rules is of paramount importance.
When May You Bend or Break the Rules?
There are only two specific circumstances under which it is at all per-
missible to bend or break the rules of proper database design. Unless
either of these is an inescapable imperative, you should use proper
database-design techniques when designing your database.
Designing an Analytical Database
As you learned in Chapter 1, an analytical database stores and tracks
historical and time-dependent data. This type of database often contains
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calculated fields within some of its table structures. The expressions
used in many of these fields are meant to record the state of a particular
set of data at a given moment in time; other fields store the results of ag-
gregate functions.
You may have already surmised from the description that this type of
database violates proper database design because its tables contain cal-
culated fields (refer to Chapter 7). In this particular instance, the viola-
tion is acceptable because of the manner in which the data in the
database is being used. I recommend that you properly design the data-
base first and then break the rules only after judicious consideration—
you should make a deliberate decision to break a rule and understand
why doing so is necessary in the specific instance.
Improving Processing Performance
This is by far the most common reason that people feel compelled to
bend or break the rules. Whenever an RDBMS takes what seems to be
an inordinate amount of time to process multitable queries or complex
reports, many people believe that the solution to the problem is to alter
the underlying table structures. For example, they would have you
modify a table in such a way that it includes every field necessary for
the query or report. While this modification does indeed increase the
speed at which the RDBMS processes the query or report, it also intro-
duces a number of new problems, such as unnecessary duplicate fields
❖ Note Designing an analytical database requires a radically dif- ferent design methodology than the one you learned in this book.
If you determine that your organization requires an analytical da-
tabase, I strongly recommend that you acquire a good book on the
subject and learn how to design such a database properly.
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When May You Bend or Break the Rules? 503
and redundant data. This is clearly not a desirable solution, because it
violates proper database design.
Unfortunately, real life is not as ideal as we would like it to be, so you
will sometimes find that you must decide between improving processing
performance and holding to proper design principles.
Is It Worth It?
When you take a moment to really think about this dilemma, you’ll soon
realize that the question really isn’t about performance; it’s about data
integrity. Anytime you break the rules for performance’ sake (or any
other reason, for that matter), you are surely going to introduce data-
integrity problems. The question you must ask yourself, then, is this: Is
the perceived increase in processing performance worth the price of re-
duced (and, therefore, weakened) data integrity? As you well know, the
consequences of making imprudent modifications to your data struc-
tures will eventually spread, like ripples in a pond, throughout your da-
tabase. Here are just a few of the problems you’ll encounter:
• Inconsistent data. This is a result of introducing unnecessary du-
plicate fields into a table. It will be your responsibility (or that of
your application program) to ensure that the data in these fields
is synchronized; if you modify the value in a particular duplicate
field, you’ll have to make certain that the same modification is
made to the remaining duplicate fields.
• Redundant data. Redundant data is also a result of introducing
unnecessary duplicate fields into a table. When you edit a particu-
lar value in a field that contains redundant data, you must be sure
to make the same modification for each instance of that value.
• Impaired data integrity. Bending or breaking the rules often violates
one or more components of overall data integrity, such as table-
level integrity and relationship-level integrity. It will be your
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responsibility (or that of your application program) to compensate
for the lack of integrity—in whatever way it manifests itself—as
best as you can.
• Inaccurate information. You cannot possibly expect the database
to provide accurate information if it has any of the aforementioned
problems.
Improving Performance by Other Means First
If you still think you want to pursue this course of action in order to im-
prove processing performance, do it only as a last resort. Before you
take these measures, however, try to improve performance by some
other means first. Consider these alternatives:
• Enhance or upgrade the computer hardware. In spite of the cost
involved, this is still the easiest way to increase processing perfor-
mance. A faster CPU, more memory, and a printer that better
meets your requirements will all help to greatly decrease the time
it takes the RDBMS to process a complex query or report. Using a
larger hard drive will also help increase the retrieval speed for
disk-intensive queries. Larger hard drives incorporate technology
that produces extremely fast disk-access times.
• Fine-tune the operating system software. Make certain that the
computer’s operating system is optimized for peak performance.
This is especially important for networked computers. You can
greatly enhance general processing performance by working with
the settings of the network’s configuration options. The types of
modifications you make to the operating system in general will de-
pend on the type of software you’re using for the operating sys-
tem, so you’ll have to refer to the software’s documentation to
determine what types of modifications you can make.
• Review the database structure. Make absolutely certain that the
database is properly designed. It makes quite a difference.
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Documenting Your Actions 505
Poorly designed databases actually contribute to poor processing
performance.
• Review the database’s implementation. Examine how the data-
base is currently implemented within the RDBMS. Make certain
you’ve taken full advantage of the RDBMS’s capabilities and de-
fined the database as efficiently and completely as possible.
• Review the application program used to work with the database.
Here’s another area you should examine very closely. Is the
application program well-written? Does it make the best use of
the tools the RDBMS provides? Are the application’s compo-
nents well-defined? In some cases, a report may print more
slowly because it is poorly designed—there may be more effec-
tive ways to design and generate the same report. Queries may
run slowly because they are improperly defined. Make certain
that each query is defined correctly and in the most efficient
way possible.
If you believe you must depart from proper database-design techniques,
carefully examine your situation. As I mentioned earlier, it’s acceptable
to suspend the rules if you are designing an analytical database. But I
still strongly recommend that you design your database properly and
thoroughly and relax the rules only for very specific reasons.
Documenting Your Actions
If you’ve exhausted all other options and still come to the conclusion that
you need to bend or break the rules, then you must document each rule
you break and each action you take! It is important that you document
your changes because doing so will compel you to think about the conse-
quences of what you are about to do and it provides a means of recording
the changes you make to the database structure. Should you decide later
that the modifications did not provide a significant increase in processing
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performance, you can use the documentation as a guide to reverse the
modifications you initially made.
These are the items that you should record:
• The reason you’re breaking the rules. Increasing processing per-
formance and decreasing the time it takes to print complex re-
ports are two of the most common reasons for breaking the rules.
Whatever your reason, be sure to state it thoroughly and clearly.
• The design principle you’re violating. Recording how you’ve altered
the database design will give you the means to reverse these
changes later should you determine that performance did not sig-
nificantly improve. You might indicate that you’re altering the
structure of a table, for example.
• The aspect of the database that you’re modifying. Indicate which
particular field, table, relationship, or view you are going to alter.
Once again, this information will be valuable should you decide to
reverse the modifications.
• The specific modifications you are making. Once you determine
which item you need to modify, record the exact modifications you
make to that item. For example, if you need to modify a relation-
ship, note the exact changes you make to its characteristics.
• The anticipated effects on the database and the application pro-
gram. Any modifications you make to the database are going to
affect all accompanying end-user application programs. For exam-
ple, altering the structure of a particular table can affect data
integrity, view structures, data-entry forms and reports built upon
the table (either partially or totally), and macros or programming
code that refer to the table. You must be sure to list every effect.
Add this document to the documentation you compiled for the database.
Even if you reverse the changes later, this record could prevent you from
yielding to a future impulse to attempt the same types of changes.
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Summary
The chapter opened by examining the two circumstances under which
you might feel compelled to depart from proper database-design tech-
niques. You learned that breaking the rules is acceptable if you are de-
signing an analytical database; otherwise, you should design the
database properly first and then make deliberate decisions to break or
bend specific rules. You then learned that the most common reason for
departing from proper design techniques is to improve processing per-
formance. Although this is not a satisfactory reason for breaking the
rules, there are times when circumstances dictate that you must con-
sider such changes.
We then continued with a discussion of the alternate measures you can
take to improve processing performance, such as enhancing or upgrad-
ing the hardware and reviewing the implementation of the database.
You learned that you should do all you can to improve performance first
and depart from proper design techniques only as a last resort. The
chapter then closed with a list of items you should record if you need to
break the rules.
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In Closing
I’m not a teacher: only a fellow-traveller of whom you asked the way. I pointed
ahead—ahead of myself as well as you. —GEORGE BERNARD SHAW
I’ve always believed that you shouldn’t have to be a rocket scientist in
order to design a database properly. It should be a relatively straightfor-
ward task that can be performed by anyone possessing a good amount
of common sense. As long as you follow a good database-design method,
you should be able to design a sound and reliable database structure.
You now possess the knowledge and skills necessary to design a rela-
tional database. You know how to define the necessary structures, es-
tablish table relationships, and implement various levels of data
integrity. If you encounter improperly or poorly designed structures,
you now know how to improve them.
Learning about database design is an ever-continuing process. You can
learn enough to design the types of databases you require, you can turn
it into a profession, or you can even make it a lifelong study. Whatever
your approach, you’ll encounter one inescapable fact: The more you
learn, the more you realize you don’t know it all. But don’t be discour-
aged; this is true of any major subject you endeavor to learn, such as
music, art, philosophy—or rocket science!
I sincerely hope you’ve enjoyed reading this book as much as I’ve en-
joyed writing it. I know that most technical books of this nature can be
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510 In Closing
a little dry, so I tried to inject a little humor every now and then, partic-
ularly in the interview and meeting dialogues. Those of you who thought
the conversations were relatively realistic are quite perceptive—they
were very loosely based on a number of interviews and conversations
I’ve had with my clients over the years.
As a parting piece of advice, let me leave you with two words: Always
learn. Never be afraid or intimidated or reluctant to learn something
new. Learning opens the door to fresh ideas, different concepts, and
new perceptions. It encourages participation and communication be-
tween individuals and broadens everyone’s horizons.
Learning is a journey that begins with but one step. You’ve taken the
first step by reading this book. Now you will continue your journey by
learning about other facets of database management.
My book ends here, but your journey is just beginning. . . .
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A Answers to
Review Questions
Chapter 1
1. The two main types of databases in use today are operational and
analytical.
2. An analytical database stores static data.
3. True. An operational database is used primarily in OLTP
scenarios.
4. The hierarchical and network database models were commonly
used in the days before the relational database model.
5. In a parent/child relationship, a parent table can be associated
with one or more child tables, but a single child table can be asso-
ciated with only one parent table.
6. A set structure is a transparent construction that establishes and
represents a relationship in a network database.
7. The relational model is based on two branches of mathematics—
set theory and first-order predicate logic.
8. A relational database stores data in relations, which the user per-
ceives as tables.
9. The three types of relationships in a relational database are one-to-
one, one-to-many, and many-to-many.
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10. You retrieve data in a relational database by using SQL.
11. The advantages of a relational database include built-in multilevel
integrity, logical and physical data independence from database
applications, guaranteed data consistency and accuracy, and easy
data retrieval.
12. A relational database management system, or RDBMS, is a soft-
ware program you use to create, maintain, modify, and manipulate
a relational database.
13. The object-relational model extends the relational database model
by incorporating various object-oriented elements and characteris-
tics, such as classes, encapsulation, and inheritance.
14. A data warehouse allows organizations to access data stored in
any number of relational and nonrelational databases.
15. XML stands for eXtensible Markup Language and is quickly becom-
ing a de facto data-transfer standard for sharing data across heter-
ogeneous systems.
Chapter 2
1. The best time to use an RDBMS program’s design tools is after you
design the logical structure of the database.
2. True. Design is crucial to the consistency, integrity, and accuracy
of data.
3. The most detrimental result of improper database design is inac-
curate information.
4. The fact that the relational database model is based on set theory
and first-order predicate logic makes the relational database struc-
turally sound and able to guarantee accurate information.
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Answers to Review Questions 515
5. These are the advantages to learning a design methodology:
a. It gives you the skills you need to design a sound database
structure.
b. It provides you with an organized set of techniques that will
guide you step-by-step through the design process.
c. It helps you keep your missteps and design reiterations to a
minimum.
d. It makes the design process easier and reduces the amount of
time you spend designing the database.
e. It will help you understand and use your RDBMS software
more fully and effectively.
6. True. Understanding database design will help you use your
RDBMS program more effectively.
7. These are the objectives of good design:
a. The database supports required and ad hoc information
retrieval.
b. The tables are constructed properly and efficiently.
c. Data integrity is imposed at the field, table, and relationship
levels.
d. The database supports business rules relevant to the
organization.
e. The database lends itself to future growth.
8. Data integrity helps to guarantee that data structures and their
values are valid and accurate at all times.
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9. These are the benefits of applying good design techniques:
a. The database structure is easy to modify and maintain.
b. The data is easy to modify.
c. Information is easy to retrieve.
d. End-user applications are easy to develop and build.
10. False. You cannot take shortcuts through some of the design pro-
cesses and still arrive at a good, sound design.
Chapter 3
1. Terminology is important for the following reasons:
a. It is used to express and define the special ideas and concepts
of the relational database model.
b. It is used to express and define the database-design process
itself.
c. It is used anywhere a relational database or RDBMS is
discussed.
2. The four categories of terms are value-related, structure-related,
relationship-related, and integrity-related.
3. The values you store in the database are data. Information is data
that you process in a manner that makes it meaningful and useful
to you when you work with it or view it.
4. A null represents a missing or unknown value.
5. The major disadvantage of nulls is that they have an adverse affect
on mathematical operations.
6. Tables are the chief structures in the database.
7. The three types of tables are data tables, linking tables, and valida-
tion tables.
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8. A view is a virtual table composed of fields from one or more base
tables in the database.
9. A key is a logical structure that you use to identify records within a
table, and an index is a physical structure that you use to optimize
data processing.
10. The three types of relationships that can exist between a pair of ta-
bles are one-to-one, one-to-many, and many-to-many.
11. You can characterize every relationship in three ways: by the
type of relationship that exists between the tables, the manner
in which each table participates, and the degree to which each
table participates.
12. A field specification represents all the elements of a field.
13. A field specification incorporates three types of elements: general,
physical, and logical.
14. Data integrity refers to the validity, consistency, and accuracy of
the data in a database.
15. The four types of data integrity are field-level, table-level, relation-
ship-level, and business rules.
Chapter 4
1. It is important to complete the design process thoroughly because
it helps you assure a sound structure and data integrity.
2. True. The level of structural integrity is in direct proportion to how
thoroughly you follow the design process.
3. The mission statement identifies the purpose of your database.
4. Mission objectives are statements that represent the general tasks
your users can perform against the data in the database.
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5. The list of fields and calculations that you compile during the sec-
ond phase of the design process constitutes your organization’s
fundamental data requirements.
6. You determine the various subjects that the tables will represent
from the mission objectives you wrote during the first phase of the
design process and the data requirements you gathered during the
second phase.
7. False. You establish field specifications for each field in the data-
base during the third phase of the database-design process.
8. You establish a logical connection between the tables in a relation-
ship either with a primary key or with a linking table.
9. The manner in which your organization views and uses its data
will determine a set of limitations and requirements that you must
build into the database.
10. You can define and implement validation tables as necessary to
support certain business rules.
11. You identify the types of views you need to build in the database by
interviewing users and management and determining how they
work with their respective data.
12. You can implement the logical database structure in an RDBMS
program after you’ve completed the entire database-design
process.
Chapter 5
1. Interviews are important because they provide a valuable commu-
nication link between you (the developer) and the people for whom
you’re designing the database. They help ensure the success of
your design efforts, and they provide critical information that can
affect the design of the database structure.
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2. The problem that arises when you conduct an interview with a
large number of people is that the intimidation level of some of the
participants will rise in direct proportion to the number of partici-
pants taking part in the interview as a whole.
3. The primary reason for conducting separate interviews with users
and management is that each group has a different perspective on
the organization as a whole and on how the organization uses its
data on a daily basis.
4. False. You’ll commonly use open-ended questions in your interviews.
5. You should try to elicit complete, descriptive responses from the
interview participants.
6. The single most important guideline for every interview you con-
duct is to always maintain control of the interview.
7. A mission statement declares the specific purpose of the database
in general terms.
8. A well-written mission statement is unambiguous, succinct and to
the point, and free of phrases or sentences that explicitly describe
specific tasks.
9. False. You must learn about the organization in order to compose
a mission statement.
10. Your mission statement is complete when you have a sentence that
describes the specific purpose of the database and that is under-
stood and agreed upon by everyone concerned.
11. A mission objective is a statement that represents a single, general
task supported by the data maintained in the database.
12. A well-written mission objective is a declarative sentence that
clearly defines a general task and is free from unnecessary details.
It is expressed in general terms, is succinct and to the point, and is
unambiguous.
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13. True. You should interview users and management to help you de-
fine mission objectives.
14. The staff’s daily work relates to the mission objectives in that many
of the tasks they perform will become mission objectives.
15. False. A mission objective cannot describe more than one task.
16. A mission objective can be derived from a response either explicitly
or implicitly.
17. A mission objective is complete when it is both properly defined
and well defined, and when it makes sense to you and to those for
whom you are designing the database
Chapter 6
1. The goals of analyzing the current database are to determine the
following:
a. What types of data the organization uses
b. How the organization uses its data
c. How the organization manages and maintains its data
2. False. You should not adopt the current database structure as the
basis for the new structure.
3. A legacy database is a database that has been in existence and in
use for five years or more.
4. The analysis process incorporates these three steps:
a. Reviewing the way data is collected
b. Reviewing the manner in which information is presented
c. Conducting interviews with users and management
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5. The types of computer software programs you should review dur-
ing the analysis include word processors, spreadsheets, data-
bases, and Web pages.
6. You should conduct interviews after you gather data-collection and
information-presentation samples for these reasons:
a. They provide details about the samples you assembled during
the previous reviews.
b. They provide information on the way the organization uses its
data.
c. They are instrumental in defining preliminary field and table
structures.
d. They help to define future information requirements.
7. You use open-ended questions to focus on specific subjects and
closed questions to focus on specific details of a certain subject.
8. The subject-identification technique allows you to identify subjects
within a participant’s response to a given question.
9. You identify specific attributes for a particular subject by using the
characteristic-identification technique.
10. False. You should interview users and management separately.
11. The three basic types of information requirements you must iden-
tify are current, additional, and future.
12. The preliminary field list represents the organization’s fundamental
data requirements and constitutes the core set of fields that you
must define in the database.
13. Each item on this list should have a unique name to ensure that
the characteristic appears only once on the list.
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14. A value list specifies the acceptable range of values for a particular
characteristic and often enforces a given business rule.
15. A calculated field stores the result of a string concatenation or
mathematical expression as its value. You should remove calcu-
lated fields from the preliminary field list and place them on a ded-
icated calculated-field list.
Chapter 7
1. You identify and establish tables for the new database using the
preliminary table list.
2. You use the preliminary field list to help you define tables for the
database because the fields on the list may imply subjects that the
database needs to track.
3. When an item on the list of subjects and a differently named item
on the preliminary table list both represent the same subject, you
select the name that best represents the subject and use it as the
sole identifier for that subject.
4. The final table list provides the name, type, and description of each
table in the database.
5. These are the guidelines for creating table names:
a. Create a unique, descriptive name that is meaningful to the
entire organization.
b. Create a name that accurately, clearly, and unambiguously
identifies the subject of the table.
c. Use the minimum number of words necessary to convey the
subject of the table.
d. Do not use words that convey physical characteristics.
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e. Do not use acronyms and abbreviations.
f. Do not use proper names or other words that will unduly
restrict the data that can be entered into the table.
g. Do not use a name that implicitly or explicitly identifies more
than one subject.
h. Use the plural form of the name.
6. These are the guidelines for composing table descriptions:
a. Include a statement that accurately defines the table.
b. Include a statement that explains why this table is important to
the organization.
c. Compose a description that is clear and succinct.
d. Do not include implementation-specific information in your
table description, such as how or where the table is used.
e. Do not make the table description for one table dependent
upon the table description for another table.
f. Do not use examples in a table description.
7. You assign fields to a table on the final table list by determining
which fields best represent characteristics of the table’s subject.
8. These are the guidelines for creating field names:
a. Create a unique, descriptive name that is meaningful to the
entire organization.
b. Create a name that accurately, clearly, and unambiguously
identifies the characteristic a field represents.
c. Use the minimum number of words necessary to convey the
meaning of the characteristic the field represents.
d. Do not use acronyms, and use abbreviations judiciously.
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e. Do not use words that could confuse the meaning of the field
name.
f. Do not use names that implicitly or explicitly identify more
than one characteristic.
g. Use the singular form of the name.
9. Poorly designed fields can cause problems with duplicate data and
redundant data.
10. You can resolve field anomalies by ensuring that the field complies
with the Elements of the Ideal Field.
11. These are the Elements of the Ideal Field:
a. It represents a distinct characteristic of the subject of the table.
b. It contains only a single value.
c. It cannot be deconstructed into smaller components.
d. It does not contain a calculated or concatenated value.
e. It is unique within the entire database structure.
f. It retains a majority of its characteristics when it appears in
more than one table.
12. Redundant data is acceptable when it is the result of resolving a
multivalued field or an unnecessary duplicate field.
13. In general terms, these are the three steps you follow to resolve a
multivalued field:
a. Remove the field from the table and use it as the basis for a
new table.
b. Use a field (or set of fields) from the original table to relate the
original table to the new table.
c. Assign an appropriate name, type, and description to the new
table and add it to the final table list.
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14. The only instance in which it is necessary to use a duplicate field
is when the field serves to establish a relationship between two
tables.
15. You can refine table structures by ensuring that each table com-
plies with the Elements of the Ideal Table.
16. These are the Elements of the Ideal Table:
a. It represents a single subject, which can be an object or event.
b. It has a primary key.
c. It does not contain multipart or multivalued fields.
d. It does not contain calculated fields.
e. It does not contain unnecessary duplicate fields.
f. It contains only an absolute minimum amount of redundant
data.
17. A subset table is a table that represents a subordinate subject of a
particular data table.
Chapter 8
1. Keys are important for the following reasons:
a. They ensure that each record in a table is properly identified.
b. They help establish and enforce various types of integrity.
c. They serve to establish table relationships.
2. The four main types of keys are candidate, primary, foreign, and
non.
3. The purpose of a candidate key is to uniquely identify a single in-
stance of the table’s subject.
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4. These are the Elements of a Candidate Key:
a. It cannot be a multipart field.
b. It must contain unique values.
c. It cannot contain null values.
d. Its value is not optional in whole or in part.
e. It comprises a minimum number of fields necessary to define
uniqueness.
f. Its values must uniquely and exclusively identify each record in
the table.
g. Its value must exclusively identify the value of each field within
a given record.
h. Its value can be modified only in rare or extreme cases.
5. True. A candidate key can be composed of more than one field.
6. Yes, a table can have more than one candidate key.
7. A field you create for the sole purpose of serving as a candidate key
is known as an artificial candidate key. You create this type of key
when there are no “naturally occurring” candidate keys in a table.
8. The primary key is the most important key you assign to a table.
9. It is important for the following reasons:
a. A primary key field exclusively identifies the table throughout
the database structure and helps establish relationships with
other tables.
b. A primary key value uniquely identifies a given record within a
table and exclusively represents that record throughout the
entire database. It also helps to guard against duplicate
records.
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10. You establish a primary key by examining the table’s pool of avail-
able candidate keys and then selecting one as the primary key.
11. These are the Elements of a Primary Key:
a. It cannot be a multipart field.
b. It must contain unique values.
c. It cannot contain null values.
d. Its value is not optional in whole or in part.
e. It comprises a minimum number of fields necessary to define
uniqueness.
f. Its values must uniquely and exclusively identify each record in
the table.
g. Its value must exclusively identify the value of each field within
a given record.
h. Its value can be modified only in rare or extreme cases.
12. Before you finalize your selection of a primary key, you must make
absolutely certain that it exclusively identifies the value of each
field within a given record.
13. An alternate key is a candidate key that was not chosen to serve as
the primary key of the table.
14. By establishing table-level integrity, you ensure the following:
a. There are no duplicate records in a table.
b. The primary key exclusively identifies each record in a table.
c. Every primary key value is unique.
d. Primary key values are not null.
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15. You should review the initial table structures for the following
reasons:
a. To ensure that the appropriate subjects are represented in the
database
b. To make certain that the table names and table descriptions
are suitable and meaningful to everyone
c. To make certain that the field names are suitable and meaning-
ful to everyone
d. To verify that all the appropriate fields are assigned to each
table
Chapter 9
1. Field specifications are important for these reasons:
a. They help establish and enforce field-level integrity.
b. They help enhance overall data integrity.
c. They compel you to acquire a complete understanding of the
nature and purpose of the data in the database.
d. They constitute the “data dictionary” of the database.
2. Field-level integrity warrants the following:
a. The identity and purpose of a field is clear, and all of the tables
in which it appears are properly identified.
b. Field definitions are consistent throughout the database.
c. The values of a field are consistent and valid.
d. The types of modifications, comparisons, and operations that
can be applied to the values in the field are clearly identified.
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3. The three categories of elements within a field specification are
general, physical, and logical.
4. The three types of specifications are Unique, Generic, and Replica.
5. Composing a field description is extremely beneficial because it
forces you (and everyone in the organization) to think carefully
about the nature of the data that will be stored in the field.
6. The Data Type element indicates the nature of the data that the
field stores.
7. The Character Support element indicates the type of characters
that a user can enter into a given field value.
8. The Display Format element governs the appearance of a field’s
value when it is displayed on a screen or printed within a document.
9. The types of keys indicated on a field specification are non, pri-
mary, alternate, and foreign.
10. False. Null does not represent a blank—it represents a missing or
unknown value.
11. The Range of Values element specifies every possible valid value for
a field.
12. An Edit Rule designates at what point in time a user can enter a
value into a field and whether he can modify that value.
13. The Comparisons Allowed element indicates the types of compari-
sons a user can apply to a given field value when he’s retrieving in-
formation from the field.
14. A value expression is some form of operation involving field values,
literal values, or a combination of both, and it returns a single
value that you can then use for a comparison operation.
15. You use a generic specification for a field that serves as a template
for other fields within the database.
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Chapter 10
1. A relationship is important for the following reasons:
a. It establishes a connection between a pair of tables that are log-
ically related to each other.
b. It helps to refine table structures and minimize redundant data
further.
c. It is the mechanism that enables you to draw data from multi-
ple tables simultaneously.
2. The three types of relationships are one-to-one, one-to-many, and
many-to-many.
3. The many-to-many relationship will pose the most problems.
4. You could possibly encounter problems such as these with a
many-to-many relationship:
a. It will be tedious and somewhat difficult for you to retrieve
information from one of the tables.
b. One of the tables will contain a large amount of redundant data.
c. Duplicate data will exist within both tables.
d. It will be difficult to insert, update, and delete data.
5. A self-referencing relationship is a relationship that exists between
the records within a given table.
6. You begin the process of identifying the relationships among the
tables in the database by creating a matrix of all the tables.
7. The two types of questions you can ask to help you identify existing
relationships are associative and contextual.
8. You use a 1:N shorthand symbol to designate a one-to-many rela-
tionship in the table matrix.
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9. You determine what type of relationship officially exists between
each pair of tables in the matrix using formulas that correspond to
the three relationship-type definitions.
10. You establish a one-to-many relationship by taking a copy of the
primary key from the table on the “one” side of the relationship
and incorporating it within the table structure on the “many” side,
where it then becomes a foreign key.
11. True. Retrieving information from tables with a self-referencing re-
lationship can be tedious and somewhat difficult.
12. You establish a self-referencing many-to-many relationship as you
would a dual-table many-to-many relationship—with a linking table.
13. You refine the foreign keys in the database by ensuring that each
one complies with the Elements of a Foreign Key.
14. The two element categories you must modify for a foreign key’s
field specification are the General Elements and Logical Elements
categories.
15. A deletion rule determines what your RDBMS should do when you
place a request to delete a given record in the parent table of the
relationship.
16. The two types of participation you can designate for a table are
Mandatory and Optional.
17. The degree of participation indicates the minimum number of
records that a given table must have associated with a single
record in the related table and the maximum number of records
that the table is allowed to have associated with a single record in
the related table.
18. A relationship attains relationship-level integrity after you’ve veri-
fied that it is properly established and its characteristics are suit-
ably set.
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Chapter 11
1. A business rule is a statement that imposes some form of con-
straint on a specific aspect of the database, such as the elements
within a field specification for a particular field or the characteris-
tics of a given relationship.
2. The two major types of business rules are database oriented and
application oriented.
3. No. Application oriented business rules impose constraints that
you cannot establish within the logical design of the database.
4. The two categories of database oriented business rules are field
specific and relationship specific.
5. A field specific business rule is one that imposes constraints on the
elements of a field specification for a particular field.
6. The constraint the business rule imposes is tested when you at-
tempt to perform one of three actions: inserting a record into the
table or an entry into a field, deleting a record from the table or a
value within a field, or updating a field’s value.
7. You document a business rule by filling out a Business Rule Spec-
ifications sheet for the rule.
8. The Business Rule Specifications sheet provides three advantages:
a. It allows you to document every database oriented business
rule.
b. It allows you to document every application oriented business
rule.
c. It provides a standard method for recording all business rules.
9. The Action Taken section of a Business Rule Specifications sheet is
the area where you indicate the modifications you’ve made to the
elements of a field specification or to a relationship diagram.
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10. A validation table (also known as a lookup table) stores data that
you specifically use to implement data integrity.
11. Validation tables usually (but not always) comprise two fields: The
first acts as the primary key and is what you’ll use to help you en-
force data integrity, and the second is simply a non-key field that
stores a set of values required by some other field in the database.
12. You can use a validation table to enforce a constraint that a busi-
ness rule imposes on a given field’s range of values.
13. You should review each Business Rule Specifications sheet to en-
sure that you’ve properly established the rule it records and that
you’ve clearly marked all of the appropriate areas on the sheet.
Chapter 12
1. You can refer to a view as a virtual table because it draws data
from base tables rather than storing data on its own.
2. Views are valuable for the following reasons:
a. You can use them to work with data from multiple tables
simultaneously.
b. They reflect the most current information.
c. You can customize them to the specific needs of an individual
or group of individuals.
d. You can use them to help enforce data integrity.
e. You can use them for security or confidentiality purposes.
3. The types of views you can define as you design the logical struc-
ture of the database are data, aggregate, and validation.
4. Each time you access a view, your RDBMS will rebuild and repop-
ulate it using the most current data from the view’s base tables.
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5. Field specifications and business rules will determine what types
of modifications you can make to a view’s data.
6. The only requirement you must fulfill in order to define a multi-
table data view is that the tables you use to create the view must
bear a relationship to each other.
7. A data view does not contain its own primary key because it is not
a table; a true table stores data and requires a primary key to serve
as a unique identifier for each of its records.
8. The purpose of an aggregate view is to display information pro-
duced by aggregating a particular set of data in a specific manner.
9. Sum, Average (arithmetic mean), Minimum, Maximum, and Count
are the most common aggregate functions that you can apply to a
set of data.
10. A grouping field is a data field within an aggregate view that
“groups” multiple instances of a given value into a single instance
of the value.
11. False. You cannot modify the data in an aggregate view because it
is composed entirely of grouping fields and calculated fields.
12. The difference between a validation table and a validation view lies
in their construction—a validation table stores its own data,
whereas a validation view draws data from its base tables.
13. You would keep the following points in mind as you identify view
requirements:
a. Review your notes with the group.
b. Review the data-entry, report, and presentation samples you
gathered during the early stages of the design process.
c. Examine the tables and the subjects they represent.
d. Analyze the table relationships.
e. Study the business rules.
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14. You should use calculated fields when they will provide pertinent
and meaningful information or when they will enhance the manner
in which the view uses its data.
15. You define a view that displays only science-fiction books by apply-
ing a filter to the appropriate field within the view.
16. You must complete a View Specifications sheet for every view in the
database because it is on this sheet that you will record the char-
acteristics of the view.
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537
B Diagram of the
Database-Design Process
The diagram on the following pages provides you with a map of the
entire database-design process. It indicates each design phase, proce-
dures within the phase, tasks within the procedure, and in some cases,
subtasks within a task.
This legend shows the type of symbols you’ll see in the diagram.
Legend
This Is a Procedure
This Is A Design Phase
this is a task
This indicates output
this is a subtask
This Represents a
Collection of Items
This Represents Written Material
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
This is a note
This Represents a Specification
Sheet
~~~~~~~
This Represents a Diagram
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Write the Mission Statement
Interview the Owner
Interview Users Interview Management
Define Mission Objectives Define Mission Objectives
Write Mission Objectives
Mission Objectives • ~~ ~~~~ ~ ~~~~~ • ~~ ~~~~ ~~~ ~~~ • ~~~ ~~~ ~~ ~ ~~~ • ~~ ~~~~ ~ ~~~~~ • ~~ ~~~~ ~~~ ~~~ • ~~~ ~~~ ~~ ~ ~~~
Define a Mission Statement and Mission Objectives
Mission Statement ~~ ~~~~ ~~~~~~ ~~ ~~~~~~ ~~~~ ~~~ ~~ ~ ~~~~~ ~~ ~~~ ~~~~~~ ~~~ ~~~ ~~
Analyze the Current Database
Data Collection Samples
Presentation Samples
Review How Data Is Collected
Review How Information Is Presented
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Interview Users
Initial List of Subjects
~~ ~~ ~~~~~ ~~~~~~ ~~~~ ~~~~~
Additional Subjects
~~ ~~ ~~~~~ ~~~~~~ ~~~~ ~~~~~
review information requirements
Verify and note data sources
review data type and usage
review the samples
current information requirements
additional information requirements
future information requirements
Data Collection Samples
with descriptions Presentation Samples
with descriptions
New Subjects
~~ ~~ ~~~~~ ~~~~~~ ~~~~ ~~~~~
Additional Data Collection and Presentation
Samples
Initial List of Characteristics
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
Additional Characteristics
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
New Characteristics
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
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additional information requirements
Additional Subjects
~~ ~~ ~~~~~ ~~~~~~ ~~~~ ~~~~~
Interview Management
review information requirements
New Subjects
~~ ~~ ~~~~~ ~~~~~~ ~~~~ ~~~~~
current information requirements
New Subjects
~~ ~~ ~~~~~ ~~~~~~ ~~~~ ~~~~~
future information requirements
New Subjects
~~ ~~ ~~~~~ ~~~~~~ ~~~~ ~~~~~
overall information requirements
Newly Discovered
Presentation Samples
New Data Collection and Presentation
Samples
Additional Data Collection and Presentation
Samples
New Characteristics
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
New Characteristics
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
New Characteristics
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
Additional Characteristics
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
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Create the Data Structures
Create a preliminary table list
Preliminary Table List 1st version
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
Compile a Complete List of Fields
create a preliminary field list
Preliminary Field List
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
review and refine list of characteristics
create a calculated field list
Calculated Field List
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
review and refine preliminary field list
Sign off on both lists
review field lists with users and management
identify implied subjects from
preliminary field list
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merge the preliminary table list
with the list of subjects
Preliminary Table List
2nd version ~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
incorporate subjects from the
mission objectives
Preliminary Table List
3rd version ~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
Define the Final Table List
refine table names
indicate table types
compose table descriptions
Final Table List ~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
interview users and management
have everyone sign off on the list
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Associate Fields with Each Table
associate fields from the preliminary field list to
each table as appropriate
List of Table Structures
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
Refine the Fields
improve field names using the appropriate guidelines
use the Elements of the Ideal Field to resolve field
anomalies
resolve multipart fields
resolve multivalued fields
List of Table Structures
with revised fields
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
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Refine the Table Structures
resolve unnecessary duplicate fields
establish subset tables
List of Table Structures
with revised tables
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
List of Table Structures
with subset tables
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
Establish Keys for Each Table
define candidate keys based on the Elements
of a Candidate Key
List of Table Structures
with candidate keys
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
use the Elements of the Ideal Table to
refine table structures
refine previously unidentified subset tables
create artificial candidate keys as necessary
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Diagram of the Database-Design Process 545
define primary keys based on the Elements
of a Primary Key
List of Table Structures
with primary keys
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
designate alternate keys from remaining
candidate keys
List of Table Structures
with alternate keys
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
review initial table structures
Initial Table Structures
~~ ~~ ~~~~ ~~~~~ ~~~ ~~~~~~ ~~~~~ ~~~~ ~~~~ ~~~~~ ~~~~~
interview users and management
have everyone sign off on the structures
with all keys
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ensure the specifications you completed are suitable and correct
meet with user/management representatives and review
all of the specifications
finish the specifications you were initially unable to complete
Define a Field Specification for Each Field in the Database
complete as many specifications as you can
have everyone sign off on the completed specifications
~~~~~~~
Complete Field Specifications
~~~~~~~
Partial Field Specifications
~~~~~~~
Field Specification Sheets
for all fields
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Diagram of the Database-Design Process 547
Determine and Establish Table Relationships
Identify Existing Relationships
create and set up a table matrix
review and refine table structures
Table Matrix
identify the official relationships for the tables
within the matrix
establish each relationship using foreign keys or linking
tables as appropriate
Refine All Foreign Keys Using the Elements of a Foreign Key
Relationship Diagrams
Revised Relationship
Diagrams
Revised Relationship
Diagrams
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Establish Relationship Characteristics
define a deletion rule
indicate the type of participation for each table
indicate the degree of participation for each table
have everyone sign off on the structures
verify relationships with user/management
representatives
Revised Relationship
Diagrams
Revised Relationship
Diagrams
Revised Relationship
Diagrams
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Diagram of the Database-Design Process 549
Define and Establish Business Rules
Field Specific Rules
identify any constraints for each field
define the necessary rules
identify the actions that test each rule
record the rule on a Business Rule Specifications
sheet
modify the appropriate field specification elements
~~~~~~~
Business Rule Specifications
~~~~~~~
Revised Field Specifications
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Relationship Specific Rules
identify any constraints for each relationship
define the necessary rules
identify the actions that test each rule
record the rule on a Business Rule Specifications
sheet
modify the appropriate relationship characteristics
Review Business Rule Specifications Sheets
revise as necessary
~~~~~~~
Business Rule Specifications
~~~~~~~
Revised Business Rule Specifications
Sheets
Relationship Diagrams
Revised
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Diagram of the Database-Design Process 551
Determine and Define Views
Identify the Organization's View Requirements
collaborate with the user/ management representatives
review the materials you've gathered and created
throughout the design process
review the tables, relationships, and business rules
View Requirements ~~ ~~~~ ~~~~~~ ~~ ~~~~~~ ~~~~ ~~~ ~~ ~ ~~~~~ ~~ ~~~ ~~~~~~ ~~~ ~~~ ~~
Define the Views
review relationship diagrams
identify the tables you need for each view
diagram the view
View Diagram
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review each of the View Specifications sheets
add calculated fields as necessary
make sure the view is properly defined and everything is in order
impose criteria to filter the data as necessary
record the view in a View Specifications sheet
have everyone sign off on the view structures
Revised View Diagram
~~~~~~~
View Specifications
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Diagram of the Database-Design Process 553
Review Data Integrity
Review Each Component of Data Integrity
field level
relationship level
business rules
view level
table level
Assemble Database Documentation
The Design Process Is Complete!
View Diagrams
Final Table List Relationship Diagrams Field Specifications Sheets Business Rule Specification Sheets Calculated Field List Table Structure Diagrams View Specification Sheets
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C Design Guidelines
Here, in alphabetical order, are the various sets of design guidelines
that appear throughout the book.
Defining and Establishing Field Specific Business Rules
1. Select a table.
2. Review each field and determine whether it requires any constraints.
3. Define the necessary business rules for the field.
4. Establish the rules by modifying the appropriate field specification
elements.
5. Determine what actions test the rule.
6. Record the rule on a Business Rule Specifications sheet.
Defining and Establishing Relationship Specific Business Rules
1. Select a relationship.
2. Review the relationship and determine whether it requires any
constraints.
3. Define the necessary business rules for the relationship.
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4. Establish the rule by modifying the appropriate relationship
characteristics.
5. Determine what actions will test the rule.
6. Record the rule on a Business Rule Specifications sheet.
Elements of a Candidate Key
• It cannot be a multipart field.
• It must contain unique values.
• It cannot contain null values.
• Its value cannot cause a breach of the organization’s security or
privacy rules.
• Its value is not optional in whole or in part.
• It comprises a minimum number of fields necessary to define
uniqueness.
• Its values must uniquely and exclusively identify each record in
the table.
• Its value must exclusively identify the value of each field within a
given record.
• Its value can be modified only in rare or extreme cases.
Elements of a Foreign Key
• It has the same name as the primary key from which it was copied.
• It uses a replica of the field specifications for the primary key from
which it was copied.
• It draws its values from the primary key to which it refers.
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Elements of a Primary Key
• It cannot be a multipart field.
• It must contain unique values.
• It cannot contain null values.
• Its value cannot cause a breach of the organization’s security or
privacy rules.
• Its value is not optional in whole or in part.
• It comprises a minimum number of fields necessary to define
uniqueness.
• Its values must uniquely and exclusively identify each record in
the table.
• Its value must exclusively identify the value of each field within a
given record.
• Its value can be modified only in rare or extreme cases.
Rules for Establishing a Primary Key
• Each table must have one—and only one—primary key.
• Each primary key within the database must be unique—no two
tables should have the same primary key unless one of them is a
subset table.
Elements of the Ideal Field
• It represents a distinct characteristic of the subject of the
table.
• It contains only a single value.
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• It cannot be deconstructed into smaller components.
• It does not contain a calculated or concatenated value.
• It is unique within the entire database structure.
• It retains the majority of its characteristics when it appears in
more than one table.
Elements of the Ideal Table
• It represents a single subject, which can be an object or event.
• It has a primary key.
• It does not contain multipart or multivalued fields.
• It does not contain calculated fields.
• It does not contain unnecessary duplicate fields.
• It contains only an absolute minimum amount of redundant
data.
Field-Level Integrity
This type of integrity ensures the following:
• The identity and purpose of a field is clear, and all of the tables in
which it appears are properly identified.
• Field definitions are consistent throughout the database.
• The values of a field are consistent and valid.
• The types of modifications, comparisons, and operations that can
be applied to the values in the field are clearly identified.
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Guidelines for Composing a Field Description
• Use a statement that accurately identifies the field and clearly
states its purpose.
• Write a clear and succinct statement.
• Refrain from restating or rephrasing the field name.
• Avoid using technical jargon, acronyms, or abbreviations.
• Do not include implementation-specific information.
• Do not make this description dependent upon the description of
another field.
• Do not use examples.
Guidelines for Composing a Table Description
• Include a statement that accurately defines the table.
• Include a statement that explains why this table is important to
the organization.
• Compose a description that is clear and succinct.
• Do not include implementation-specific information in your table
description, such as how or where the table is used.
• Do not make the table description for one table dependent upon
the table description for another table.
• Do not use examples in a table description.
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Guidelines for Creating Field Names
• Create a unique, descriptive name that is meaningful to the entire
organization.
• Create a name that accurately, clearly, and unambiguously iden-
tifies the characteristic a field represents.
• Use the minimum number of words necessary to convey the mean-
ing of the characteristic the field represents.
• Do not use acronyms, and use abbreviations judiciously.
• Do not use words that could confuse the meaning of the field
name.
• Do not use names that implicitly or explicitly identify more than
one characteristic.
• Use the singular form of the name.
Guidelines for Creating Table Names
• Create a unique, descriptive name that is meaningful to the entire
organization.
• Create a name that accurately, clearly, and unambiguously iden-
tifies the subject of the table.
• Use the minimum number of words necessary to convey the sub-
ject of the table.
• Do not use words that convey physical characteristics.
• Do not use acronyms and abbreviations.
• Do not use proper names or other words that will unduly restrict
the data that can be entered into the table.
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• Do not use a name that implicitly or explicitly identifies more than
one subject.
• Use the plural form of the name.
Identifying Relationships
Use this procedure to identify the official relationship between a pair of
tables within a table matrix:
1. Select a pair of tables and note the entry at the junction of the first
table and the second table.
2. Locate the second table on the same side of the matrix you’re
working on and note the entry and the junction between it and the
first table on the opposite side of the matrix.
3. Apply the appropriate formula (shown below) to the two entries
and identify the official relationship between the tables.
a. 1:1 + 1:1 = 1:1
b. 1:N + 1:1 = 1:N
c. 1:N + 1:N = M:N
4. Diagram the relationship in the appropriate manner.
5. Cross out both entries on the matrix.
Identifying View Requirements
Use this procedure to identify your organization’s view requirements:
• Review your notes with the group of user/management
representatives.
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• Review the data-entry, report, and presentation samples you
gathered during the early stages of the design process.
• Examine the tables and the subjects they represent.
• Analyze the table relationships.
• Study the business rules.
Interview Guidelines
Participant Guidelines
• Make the participants aware of your intentions.
• Let the participants know that you appreciate their taking part in
the interview and that their responses to the interview questions
are valuable to the overall design project.
• Make sure everyone understands that you are the official arbitra-
tor if and when a dispute arises.
Interviewer Guidelines
• Conduct the interview in a well-lit room, separated from distract-
ing noise, with a large table and comfortable chairs, and have cof-
fee and munchies on hand.
• Set a limit of 10 people or fewer for each interview.
• Conduct separate interviews for users and management.
• When you have to interview several groups of people, designate a
group leader for each group.
• Prepare your questions prior to the interview.
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• If you’re not very good at taking notes, either assign that task to a
dependable transcriber for each interview or get the group’s per-
mission to use a tape recorder to record the interview.
• Give everyone your equal and undivided attention.
• Keep the pace of the interview moving.
• Always maintain control of the interview.
Mission Statements
A well-written mission statement has the following attributes:
• It expresses its point succinctly and immediately.
• It avoids unnecessary statements or details and is well-defined.
• It avoids phrases or sentences that explicitly describe specific
tasks.
• It makes sense to you (the database developer) and to those for
whom you are designing the database.
Mission Objectives
A well-written mission objective has the following attributes:
• It comprises a declarative sentence that clearly defines a general
task and is free from unnecessary details.
• It expresses itself in general terms that are succinct, to the point,
and unambiguous.
• It makes sense to you and to those for whom you are designing
the database.
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Relationship-Level Integrity
This type of integrity ensures the following:
• The connection between the two tables (or key fields) in a relation-
ship is sound.
• You can insert new records into each table in a meaningful
manner.
• You can delete an existing record without producing any adverse
affects.
• There is a meaningful limit to the number of records that can be
interrelated within the relationship.
Resolving a Multivalued Field
Use this generic procedure to resolve a multivalued field:
1. Remove the field from the table and use it as the basis for a new
table. If necessary, rename the field in accordance with the field
name guidelines that you learned earlier.
2. Take the primary key from the original table and incorporate
it into the new table structure. This field will perform two
specific functions in the new table: It will serve as part of the
table’s composite primary key, and it will serve as a foreign key
that helps to establish the relationship between the new table
and the original table.
3. Assign an appropriate name, type, and description to the new table
and add it to the final table list.
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Table-Level Integrity
This type of integrity ensures the following:
• There are no duplicate records in a table.
• The primary key exclusively identifies each record in a table.
• Every primary key value is unique.
• Primary key values are not null.
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D Documentation Forms
Blank copies of the Field Specifications sheet, Business Rule Specifica-
tions sheet, and View Specifications sheet are provided here for you to
copy and use on your database projects.
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Field Name:
Label:
Parent Table:
Shared By:
Alias(es):
Description:
Specification Type:
Source Specification:
ReplicaUnique Generic
Length:
Decimal Places:
Input Mask:
Display Format:
Data Type: Character Support:
Letters (A–Z)
Numbers (0–9)
.Keyboard ( , / $ # %)
Special ( © ® ™ ∑ π)
Key Structure:
Non
Not Determined At This Time
Edit Rule:
Null Support: Nulls Allowed
Enter Now, Edits Allowed
Enter Now, Edits Not Allowed
Enter Later, Edits Allowed
Primary
AlternateForeign
No Nulls
Uniqueness: Non-unique Unique
Required Value: No Yes
Comparisons Allowed:
Range of Values:
Default Value:
Values Entered By: User
Operations Allowed:
System
Key Type:
CompositeSimple
Enter Later, Edits Not Allowed
<> ≠ <=>= Other Fields
Same Field =
Value Expression
<> ≠ <=>== <> ≠ <=>==
All
All
All
÷Same Field Other Fields Concatenation÷
All
All
+
+
x
x
Value Expression All Concatenation÷+ x
Concatenation
General Elements
Physical Elements
Logical Elements
FIELD SPECIFICATIONS
–
–
–
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Field Names:
Table Names:
Statement:
Constraint:
Test On: Insert
Delete
UpdateCategory: Field Specific
Relationship Specific
Type: Database Oriented
Application Oriented
Logical Elements
Key Structure
Edit Rule
Null Support
Uniqueness
Required Value
Comparisons Allowed
Range of Values
Default Value
Values Entered By
Operations Allowed
Key Type
Physical Elements
Length
Input MaskDecimal Places
Character Support Display Format
Data Type
Degree of ParticipationType of ParticipationDeletion Rule
Action Taken
Structures Affected
Rule Information
Field Elements Affected
Relationship Characteristics Affected
BUSINESS RULE SPECIFICATIONS
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Base Tables
General Information
Description:
Calculated Field Expressions
Field Name
Filters
Field Name Condition
Expression
Name: Type: Data ValidationAggregate
VIEW SPECIFICATIONS
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E Database-Design
Diagram Symbols
The symbols I’ve used throughout the book to diagram data structures,
relationships, relationship characteristics, and key designations are
presented here for quick and easy reference.
DATA TABLE
SUBSET TABLE VALIDATION TABLE
LINKING TABLE VIEW
Table and View Structures
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Relationship Types
One-to-One
One-to-Many
Many-to-Many
Dual Table Single Table
(C) Cascade
(D) Deny
Deletion Rules
(N) Nullify
(R) Restrict
(S) Set Default
Type of Participation
Mandatory Participation
Optional Participation
Degree of Participation
(1,8)
Minimum number of related records allowed
Maximum number of related records allowed
PK Primary Key
CCK Composite Candidate KeyCK Candidate Key
AK Alternate Key
FK Foreign Key
Key Designations
CFK Composite Foreign Key
CAK Composite Alternate Key
CPK Composite Primary Key
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F Sample Designs
I’ve provided these sample designs to serve as ideas for databases you
may want or need to create. I emphasize the word “ideas” because five
people can look at the same design and come up with five distinct varia-
tions based on their needs, backgrounds, and personal points of view.
Remember that there is no right or wrong way to design a given data-
base, but you do have to ensure that the tables, fields, relationships,
and views all conform to the guidelines you’ve learned from this book.
I intentionally omitted all but the primary and foreign key fields from
each table because I did not want to greatly influence you in any way as
to how the tables should be populated. I also omitted a majority of the
relationship characteristics for the same reason.
Should you see a design that you might be able to use, run it through
the entire database-design process and treat it like an existing data-
base. At the end of the process, you should have a database that suits
your needs.
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Entertainment Agency Database
Customers
Customer ID PK
Agents
Agent ID PK
Members
Member ID PK
Entertainer Members
Entertainer ID CPK/FK Member ID CPK/FK
Musical Preferences
Customer ID CPK/FK Style ID CPK/FK
Musical Styles
Style ID PK
Entertainers
Entertainer ID PK
Entertainer Styles
Customer ID CPK/FK Style ID CPK/FK
Engagements
Engagement ID PK Customer ID FK Agent ID FK Entertainer ID FK
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School Database
Staff
Staff ID PK
Faculty
Staff ID PK
Faculty Categories
Staff ID CPK/FK Category ID CPK/FK
Faculty Classes
Class ID CPK/FK Staff ID CPK/FK
Faculty Subjects
Staff ID CPK/FK Subject ID CPK/FK
Subjects
Subject ID PK
Departments
Department ID PK
Classroomes
ClassRoom ID PK
Buildings
Building Code PK
Students
Student ID PK
Student Class Status
Class Status PK
Building Code FK
Categories
Category ID PK Department ID FK
Category ID FK
Classes
Class ID PK Subject ID FK Classroom ID FK
Student Schedules
Class ID CPK/FK Student ID CPK/FK Class Status FK
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Sales Order Database
Customers
Customer ID PK
Employees
Employee ID PK
Orders
Order ID PK Customer ID FK Employee ID FK
Products
Product Number PK Category ID FK
Order Details
Order ID CPK/FK Product Number CPK/FK
Categories
Category ID PK
Product Vendors
Product Number CPK/FK Vendor ID CPK/FK
Vendors
Vendor ID PK
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Office Inventory Database
Software
Item ID PK
Office Furniture
Item ID
Office Equipment
Item ID
Items
Item ID PK
Container Items
Container ID CPK/FK Item ID CPK/FK
Containers
Container ID PK Storage Location ID FK
Storage Locations
Storage Location ID PK
PK
PK
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Bowling League Database
Matches
Match ID PK Tournament ID FK Odd-lane Team ID FK Even-lane Team ID FK
Tournaments
Tournament ID PK
Teams
Team ID PK
Bowlers
Bowler ID PK
Team Members
Team ID CPK/FK Bowler ID CPK/FK
Matches
Match ID CPK Game Number CPK Winning Team ID FK
Bowler Scores
Match ID CPK Game Number CPK Bowler ID CPK
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Car Rental Database
Customers
Customer ID PK
Vehicles
License Number PK
Employees
Employee ID PK
Supervisor ID FK
Locations
Location ID PK
Maintenance Types
Maintenance Type ID PK
Maintenance Workorders
Workorder Number PK License Number FK Maintenance Type ID FK
Rentals
Rental ID PK Customer ID FK Employee ID FK Location ID FK License Number FK
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G Recommended Reading
Should you be interested in pursuing an in-depth study of database
technology, here are my recommendations for books on this subject. I’ve
chosen these particular books because they have stood the test of time
and have become standard reading within the database industry and
academic institutions. (I’m pleased to state that my book has become
part of this notable list.) Keep in mind that most of these books are go-
ing to be challenging to read; the authors presume that you have a fair
amount of background in computers and programming or are pursuing
a degree in computer science.
Codd, E. F. (1990). The Relational Model for Database Management: Ver-
sion 2. Reading, MA: Addison-Wesley. (Note: This book is hard to
find, but it’s worth having in your library if you’re going to become
a serious database developer.)
Connolly, Thomas, and Carolyn Begg. (2002). Database Systems—A
Practical Approach to Design, Implementation, and Management,
Third Edition. Boston, MA: Addison-Wesley.
Date, C. J. (2000). An Introduction to Database Systems, Seventh
Edition. Boston, MA: Addison-Wesley.
——. (2000). The Database Relational Model—A Retrospective Review
and Analysis. Boston, MA: Addison-Wesley.
Date, C. J., and Hugh Darwen. (2000). Foundation for Future Database
Systems—The Third Manifesto, Second Edition. Boston, MA:
Addison-Wesley.
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582 Recommended Reading
Fleming, Candace C., and Barbara von Halle. (1989). Handbook of Rela-
tional Database Design. Reading, MA: Addison-Wesley.
Hoffer, Jefferey A., Mary B. Prescott, and Fred R. McFadden. (2002).
Modern Database Management, Sixth Edition. Upper Saddle River,
NJ: Prentice Hall.
Kroenke, David M. (2000). Database Processing—Fundamentals, Design,
& Design, Seventh Edition. Upper Saddle River, NJ: Prentice Hall.
I do recommend other books on a variety of subjects, such as database
design and theory, data modeling, GUI design, SQL, Visual Basic, and
.NET. You can review these recommendations by accessing my Web site
at http://www.ForMereMortals.com.
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Glossary
Aggregate Function A snippet of programming code that executes a
particular type of mathematical aggregation on a set of data and re-
turns a single value.
Aggregate View A view used to display information produced by ag-
gregating a particular set of data in a specific manner.
Alternate Key A candidate key that has not been designated as a pri-
mary key.
Analytical Database A type of database that stores static data and is
used when there is a need to track trends, view statistical data over
a long period of time, or make tactical or strategic business projec-
tions; it is typically associated with OLAP.
Application A commercial or custom-built software program that is
typically used to provide a user-friendly interface for a database.
Application Development The process of designing and creating an
application that will serve as the user interface for a database.
Application Program Commercial or custom-built software that
serves as the user-interface to a database.
Application Oriented Business Rule A rule that imposes con-
straints that you must establish within the physical design of the
database or within the design of the database application.
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Artificial Candidate Key A field created for the sole purpose of serv-
ing as a candidate key. It’s existence is due to an absence of any
“naturally occurring” candidate keys within the table.
Associative Table See Linking Table.
Attribute The relational model’s equivalent of a field.
Base Tables Tables that form the basis of a view.
Business Rule Specification Represents all of the characteristics of
a business rule, such as the rule statement, the constraint it im-
poses, the structures it affects, and so on.
Business Rules Restrictions or limitations on certain aspects of a
database based on the ways an organization perceives and uses
its data.
Calculated Field A field that contains a concatenated text value or
the result of a mathematical expression.
Calculated-Field List A list of fields that can be defined only within
an RDBMS. (Recall that you cannot define calculated fields within a
table structure.)
Cardinality The type of relationship that exists between a pair of ta-
bles in a relational database. See Relationship.
Child Table Within a given relationship, a table containing records
that are explicitly dependent upon the existence of records in the re-
lated table.
Client/Server RDBMS A type of RDBMS in which data resides on a
computer acting as a database server and users interact with the
data through applications residing on their own computer, known
as the database client.
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Closed Question A question that has a definitive, finite set of answers.
This type of question leaves little opening for further follow-up
questions.
Command Prompt A set of one or more symbols indicating the area
within an operating system or command-driven software program in
which a user can enter and execute commands. For example, C:\>
is a command prompt within the MS-DOS operation system, and R>
is the command prompt within R:BASE Technologies’ R:BASE data-
base software.
Composite Primary Key A primary key composed of two or more
fields.
Data The values stored in the database.
Data Consistency Every occurrence of a given field value throughout
the entire database is exactly the same.
Data-Entry Form A screen within an application program used to
gather and collect data.
Data Integrity A set of rules or guidelines that governs the validity,
consistency, and accuracy of the data in a database. There are four
types of data integrity: table-level, field-level, relationship-level, and
business rules.
Data Structure A particular construct used to store data, such as a
field or table.
Data Table A table that stores data used to supply information; it is
the most common type of table in a relational database.
Data View A view used to examine and manipulate data from one or
more base tables.
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Database Application Program See Application Program.
Database Developer A person who designs and implements a
database.
Database-Design Process The set of actions required to design the
logical structure of a database.
Database Oriented Business Rule A rule that imposes constraints
that you can establish within the logical design of the database.
DBMS (Database-Management System) A software program that is
used to create, maintain, modify, and manipulate a database.
Degree of Participation Considering a given relationship between a
pair of tables within a relational database, this is the minimum and
maximum number of records that one table can have associated
with a single record in the related table.
Deletion Rule A rule that determines what the RDBMS should do
when a user places a request to delete a given record in the parent
table of a relationship.
Domain See Field Specification.
Domain Integrity See Field-Level Integrity.
Duplicate Data A nonprimary key value that appears in more than
one table within the database.
Duplicate Field A field that appears in two or more tables for any of
these reasons: It is used to relate a set of tables together; it indicates
multiple occurrences of a particular type of value; or there is a per-
ceived need for supplemental information.
Dynamic Data Data that changes constantly and always reflects up-
to-the-minute information.
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Glossary 587
Elements of a Candidate Key This is a set of guidelines used to de-
termine whether a given field is fit to serve as a candidate key.
Elements of a Foreign Key This is a set of guidelines used to deter-
mine whether a given field is fit to serve as a foreign key.
Elements of a Primary Key This is a set of guidelines used to deter-
mine whether a given candidate key field is fit to serve as a primary
key.
Elements of the Ideal Field A set of guidelines used to create sound
field structures and to help identify poorly designed fields.
Elements of the Ideal Table A set of guidelines used to create sound
table structures and to help identify poorly designed tables.
End User A person who uses and works with a database or database
application program.
End-User Application Commercial or custom-built software that
serves as the user interface to a database.
Entity Integrity See Table-Level Integrity.
Event Something that occurs at a given point in time (such as a doc-
tor’s appointment or stock transaction) that can be represented by a
table.
Explicit Information Information that is clearly stated within the re-
sponse to a given question.
Extended Data Types Additional data types provided by many RDBMS
programs that go beyond those specified by the SQL Standard.
Field The smallest structure in the database. It represents a character-
istic of the subject of the table to which it belongs and is the only
structure that actually stores data within the database.
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588 Glossary
Field Specification Represents all of the general, physical, and logical
elements of a field. (This is traditionally known as a domain.)
Field-Level Integrity This type of data integrity warrants the following:
the identity and purpose of a field is clear and all of the tables in
which it appears are properly identified; field definitions are consis-
tent throughout the database; the values of a field are consistent and
valid; and the types of modifications, comparisons, and operations
that can be applied to the values in the field are clearly identified.
Field Specific Business Rule A rule that imposes constraints on the
elements of a field specification for a given field.
Filter A set of one or more constraints imposed on a view that causes it
to return a specific set of information.
Final Table List This list contains key information (name, type, and
description) on every table in the database.
First-Order Predicate Logic One of the two branches of mathematics
upon which the relational model is based.
Hierarchical Database A database in which data is structured hier-
archically and is typically diagrammed as an inverted tree.
Implementation Process The set of actions required to take a logical
database design and incorporate it within a specific RDBMS.
Implicit Information Information that is not expressly stated within a
response to a given question; you must derive it from your examina-
tion of the response.
Index A structure within an RDBMS program that can be used to im-
prove data processing.
Information Data that is processed in a manner that makes it mean-
ingful and useful to the person working with it or viewing it.
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Glossary 589
Information Requirements Information that must be supported by
the data in the database in order for the organization to function
properly, effectively, and efficiently.
Inherited Database See Legacy Database.
Keys Special fields that play very specific roles within a table; the type
of key determines its purpose within the table. There are four signif-
icant types of key: candidate, primary, alternate, and foreign.
LAN See Local Area Network.
Legacy Database A database that has been in existence and in use
for several years or more.
Linking Table A table that helps to establish a many-to-many rela-
tionship between a given pair of tables.
List of Characteristics A collection of nouns that imply various at-
tributes of the items on the List of Subjects.
List of Subjects A collection of nouns that represent subjects that
may be of interest to the organization.
Local Area Network (LAN) A group of computers and peripherals lo-
cated within a relatively limited geographical area that share ser-
vices and resources.
Logical Child Relationship A relationship that exists between a
given table in one hierarchical database and another table in a sec-
ond hierarchical database.
Logical Data Independence Changes made to the logical design of
the database will not adversely affect the applications built upon the
database.
Lookup Table See Validation Table.
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590 Glossary
Mainframe Computer A large, high-end, extremely powerful computer
designed to handle literally millions of highly intensive computa-
tions simultaneously.
Many-to-Many Relationship A relationship between a pair of tables
in a relational database in which a single record in the first table
can be related to many records in the second table and a single
record in the second table can be related to many records in the
first table.
Member The subordinate node in a given relationship within a network
database.
Missing Value A data value that has not been entered into a given field
due to human error.
Mission Objective A statement that represents a general task that a
user will perform against the data in the database.
Mission Statement A statement that establishes the purpose of the
database and provides a distinct focus for your design work.
Multilevel Integrity This incorporates two or more of the following:
field-level integrity, table-level integrity, relationship-level integrity,
and business rules.
Multipart Field A field that contains more than one type of distinct
value.
Multivalued Field A field that contains multiple instances of the same
type of value.
Network Database A database in which data is structured hierarchi-
cally and is typically diagrammed as an inverted tree. Unlike the hi-
erarchical database, however, it can contain several inverted trees
that share branches.
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Glossary 591
Node A given collection of records within a network database.
Non-key A field that does not serve as a candidate, primary, alternate,
or foreign key.
Normal Form A specific set of rules that can be used to test a table
structure to ensure that it is sound and free of problems.
Normalization The process of decomposing large tables into smaller
ones in order to eliminate redundant data and duplicate data.
Null This represents a missing or unknown value; it does not represent
a zero or a text string of one or more blank spaces.
Object A tangible item (such as a person, place, or thing) that can be
represented by a table.
OLAP (On-Line Analytical Processing) A method of presenting data
from an analytical database in which the data is summarized and
presented in the form of a table or cube.
OLTP (On-Line Transaction Processing) A system for processing
transactions as soon as the computer receives them and updating
master files immediately in a database-management system.
One-to-Many Relationship A relationship between a pair of tables in a
relational database in which a single record in the first table can be
related to many records in the second table, but a single record in
the second table can be related to only one record in the first table.
One-to-One Relationship A relationship between a pair of tables in a
relational database in which a single record in the first table is re-
lated to only one record in the second table, and a single record in
the second table is related to only one record in the first table.
On-Line Analytical Processing See OLAP.
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592 Glossary
On-Line Transaction Processing See OLTP.
Open-Ended Question A question that can be answered in a variety of
ways and can lead to further follow-up questions.
Operating System The complete set of software required to manage
and provide services for the computer’s hardware, peripheral equip-
ment (such as printers and scanners), and all other software pro-
grams. The computer cannot function without the operating system.
Operational Database A type of database that stores dynamic data
and is used in situations where there is a need to collect, modify,
and maintain data on a daily basis; it is typically associated with
OLTP.
Orphaned Record Given two related tables, this is a record in one ta-
ble that is not associated with any record in the other table.
Owner The main node in a given relationship within a network database.
Owner/Member Relationship A type of relationship in a network da-
tabase in which an owner table can be associated with one or more
member tables, but a single member table must be associated with
a specific owner table.
Paper-Based Database A loose collection of forms, index cards, ma-
nila folders, and so on, used to collect and maintain data.
Parent/Child Relationship A type of relationship in a hierarchical
database in which a parent table can be associated with one or more
child tables, but a single child table can be associated with only one
parent table.
Parent Table Within a given relationship, a table containing records
that are not dependent upon the existence of records in the related
table.
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Glossary 593
Parse To decompose a given data value into smaller, distinct parts.
Physical Data Independence Changes the database software vendor
makes to the physical implementation of the database will not ad-
versely affect the applications built upon the database.
Pointer A mechanism that explicitly links a parent table to a child table
in a hierarchical database.
Preliminary Field List A list of fields that represents the organiza-
tion’s fundamental data requirements and constitutes the core set
of fields that must be defined in the database.
Preliminary Table List The core set of tables that must be defined in
the database.
Primary Key A field or group of fields that uniquely identifies each
record within a table.
Programming Environment The combination of a given computing
platform (PC, client/server, mainframe, etc.), operating system, and
programming language.
Programming Language A software program that can be used to de-
fine sets of instructions that will ultimately be processed and exe-
cuted by the computer.
Query A request for information posed to the database via an SQL
query statement.
Query Builder A tool within a database software program that allows a
user to build a query via an easy-to-use graphical interface.
RDBMS (Relational Database Management System) A software
program that is used to create, maintain, modify, and manipulate a
relational database.
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594 Glossary
Record A structure that is composed of a complete set of singular val-
ues (regardless of whether any are null) for every field within a table
and represents a unique instance of the table’s subject.
Recursive Relationship See Self-Referencing Relationship.
Redundant Data A value that is repeated in a field as a result of the
field’s participation in relating two tables or as a result of some field
or table anomaly.
Reference Field See Duplicate Field.
Referential Integrity See Relationship-Level Integrity.
Relation The relational model’s equivalent of a table.
Relational Database A type of database that stores data in relations
(perceived by the user as tables). Each relation is composed of tu-
ples (records) and attributes (fields).
Relational Database Management System See RDBMS.
Relational Model A data model based on set theory and first-order
predicate logic invented by Dr. Edgar F. Codd.
Relationship An interdependence that exists between two tables when
records in the first table can in some way be associated with records
in the second table. There are three types of relationships in a rela-
tional database: one-to-one, one-to-many, and many-to-many.
Relationship Diagram A graphic representation of the relationship
between a given pair of tables or between a given set of records
within a table.
Relationship-Level Integrity A type of data integrity that ensures
that the relationship between a pair of tables is sound and that the
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Glossary 595
records in the tables are synchronized whenever data is entered
into, updated in, or deleted from either table.
Relationship Specific Business Rule A rule that imposes con-
straints that affect the characteristics of a relationship.
Report Any hand-written, typed, or computer-generated document
used to arrange and present data in such a way that it is meaningful
to the person or people viewing it.
Root Table The topmost table in a hierarchical database structure.
Screen Presentation A series of screens that discuss various topics in
an organized manner.
Self-Referencing Many-to-Many Relationship A relationship that
exists when a given record in a table can be related to one or more
other records within the table and one or more records can them-
selves be related to the given record.
Self-Referencing One-to-Many Relationship A relationship that ex-
ists when a given record in a table can be related to one or more
other records within the table.
Self-Referencing One-to-One Relationship A relationship that ex-
ists when a given record in a table can be related to only one other
record within the table.
Self-Referencing Relationship A relationship that exists between the
records within a table. Similar to its dual-table counterpart, a self-
referencing relationship can be one-to-one, one-to-many, or many-
to-many.
Set Structure A transparent construction that establishes and repre-
sents a relationship within a network database.
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596 Glossary
Set Theory One of the two branches of mathematics upon which the
relational model is based.
SQL (Structured Query Language) A standardized language used to
create, maintain, modify, and query relational databases.
Static Data Data that is never (or very rarely) modified.
Structural Integrity A set of rules or guidelines that governs the
manner in which fields, tables, and views are defined.
Structured Query Language See SQL.
Subset Table A table that represents a subordinate subject of a partic-
ular data table.
Table The chief structure in a database. It is composed of fields and
records and always represents a single, specific subject.
Table Description A statement that provides a clear definition of the
subject represented by the table and states why the subject is im-
portant to the organization.
Table-Level Integrity This type of data integrity ensures that a table is
free of duplicate records and that the values of the table’s primary
key are unique, never null, and exclusively identify the table records.
Tuple The relational model’s equivalent of a record.
Type of Participation The manner in which a table participates
within a given relationship in a relational database. The type of par-
ticipation can be either mandatory or optional.
Type of Relationship The manner in which a given pair of tables can
be related (one-to-one, one-to-many, many-to-many).
Unknown Value A value for a specific field that has yet to be deter-
mined or defined.
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Glossary 597
URL An acronym for Uniform Resource Locator. It represents an
address for a given resource on the Internet, such as http://
www.ForMereMortals.com.
Validation Table A table that stores data specifically used to imple-
ment data integrity. (This is also known as a lookup table.)
Validation View A view used specifically to implement data integrity.
View A virtual table composed of fields from one or more base tables in
the database.
View Specification Represents all of the characteristics of a view,
such as the name, type, base tables, and so on.
WAN See Wide Area Network
Web Page A document consisting of a Hypertext Markup Language
(HTML) file and associated support files that can be accessed via the
Internet.
Wide Area Network (WAN) A group of computers and peripherals lo-
cated over a widespread geographic area that depends on various
communications devices to share services and resources.
Zero-Length String Two consecutive single quotes with no space in
between them.
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References
Codd, E. F. (1990). “Relational Philosopher.” DBMS December 1990,
34–40, 60.
———. (1990). The Relational Model for Database Management Version
2. Reading, MA: Addison-Wesley.
Connolly, Thomas, and Carolyn Begg. (2002). Database System: A Prac-
tical Approach to Design, Implementation and Management, Third
Edition. Boston, MA: Addison-Wesley.
Date, C. J. (1994). “According to Date: Many Happy Returns!” Database
Programming and Design. September 1994, 19–22.
———. (2000). An Introduction to Database Systems, Seventh Edition.
Boston, MA: Addison-Wesley.
Fleming, Candace C., and Barbara von Halle. (1989). Handbook of Rela-
tional Database Design Reading, MA: Addison-Wesley.
Hoffer, Jeffrey A., Mary B. Prescott, and Fred R. McFadden. (2002).
Modern Database Management, Sixth Edition. Upper Saddle River,
NJ: Prentice Hall.
Kalman, David. (1994). “Moving Forward with Relational” DBMS, Octo-
ber 1994, 62–74, 109.
Kroenke, Dr. David M. (2000). Database Processing Fundamentals,
Design and Implementation, Seventh Edition. Upper Saddle River,
NJ: Prentice Hall.
From the Library of Stephen Benoit
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600 References
McGoveran, David. (1994) “The Relational Model Turns 25.” DBMS
October 1994, 46–61.
Pascal, Fabian. (2000) Practical Issues in Database Management: A Ref-
erence for the Thinking Practitioner. Boston, MA: Addison-Wesley.
Stephens, Ryan K., and Ronald R. Plew. (2001) Database Design. India-
napolis, IN: Sams.
Teorey, Toby J. (1999) Database Modeling & Design, Third Edition. San
Francisco, CA: Morgan Kaufmann.
From the Library of Stephen Benoit
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601
Index
Abbreviations in field names, 210 in field specifications, 292 in final table list, 195–96
Acronyms in field names, 210 in field specifications, 292 in final table list, 195–96
Action-oriented questions, 344 Addition (+), 306 Aerodynamic theories, 31 Aggregate views, 454–58 Aliases, 289–91 Alphanumeric data, 296 Alternate keys, 268, 300 American National Standards
Institute (ANSI), 22, 294 Analytical database, 4–5
designing, 501–2 Anomalies, using ideal field to resolve,
213–16 Ansa Software, 19 Application development, xiiii Application oriented business rules,
407–9 Application problems, xxxviii–xxxix Application program, reviewing, 505 Approximate numeric data type, 295 Artificial candidate keys, 259–61 Ashton-Tate, 19 Associative questions, 343 Associative tables, 62 Attributes, 52, 55
Base tables, 57, 447, 469 Bit data type, 295 Blank spaces, 47 Business rules, 72, 403–45
application oriented, 407–9 categories of, 409–12 database oriented, 407 defined, 404–7 defining and establishing, 412–28 determining and defining, 84–85 field specific, 409–10, 412–13, 555 relationship specific, 410–12,
555–56 reviewing and refining data integ-
rity at level of, 484–85 types of, 407–9 validation tables in supporting,
431–34 Business Rule Specifications sheet,
569 recording rule on, 419–21, 427–28 reviewing, 434–36
Calculated-field list, 170–71, 171 Calculated fields, 55, 464–67, 469
in flat-file design, 493 California, University of, at Berkeley,
19 Candidate keys, 253–61
artificial, 259–61 composite, 257 elements of, 253–59, 556 surrogate, 259
From the Library of Stephen Benoit
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602 Index
Cascade deletion rule, 382 Character-based user interface
screens, 121 Character data type, 294 Characteristic-identification tech-
nique, 140–41, 156, 160 Character support, 297–98 Classes, 22 Closed question, 97 Codd, Dr. Edgar F., 12–13 Comparisons allowed, 305–6 Composite candidate key, 257, 361 Composite primary key, 59, 66,
266–67 Computer-aided design (CAD), 21 Computer-Assisted Software Engi-
neering (CASE) software, 206 Computer hardware, enhancing or
upgrading, 504 Concatenation, 307 Contextual questions, 344–45 Criteria, imposing, in filtering data,
467–68 Current database, analysis of, 80–82,
119–78
Data, 45 collection of, in database analysis,
125–29 consistency of, 17 dynamic, 4 imposing criteria to filter, 467–68 inconsistent, 503 logical, 17 physical, 17 redundant, 124, 226, 503 retrieving, 15–16 static, 4, 45
Database(s). See also Relational databases
analysis of current, 80–82, 119–78 analytical, 4–5, 501–2 application problems in,
xxxviii–xxxix
assembling documentation for, 486–87
data problems in, xxxix defined, 4 defining field specification for each
field in, 314–18 future for, 22–24 hierarchical, 5–9 human-knowledge, 121 inherited, 80 legacy, 80, 121, 122, 123–25 mainframe, 123–24 object-oriented, 21 object-relational, 21 operational, 4, 5 paper-based, 80, 120–21, 122, 123 PC-based legacy, 124 relational, 3–25, 124 reviewing implementation, 505 reviewing structure, 504–5
Database analysis, 80–82 compiling list of fields in, 162–77 data collection in, 125–29 getting to know current database,
119–25 information presentation in, 129–33 interviews in, 133–42
of management, 157–62 of users, 142–57
Database client, 20 Database design, xxxvii
advantage of learning a good meth- odology, 31–32
analysis of current database, 80–82 bending or breaking rules, 501–7 benefits of good, 33–34 conducting interviews in, 91–100 creating the data structures, 82–83 database software as basis for,
497–98 data modeling in, 34, 35–36 determining and defining business
rules, 84–85 determining and defining views, 85
From the Library of Stephen Benoit
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Index 603
determining and establishing table relationships, 83–84
diagram of, 537–54 symbols in, 571–72
importance of completing, 78–79 making choices in, 404 methods of, 34–39 mission objectives in, 79–80,
108–15, 182, 189–91, 563 mission statement in, 79–80,
101–8, 563 normalization phase in, 34, 36, 39 objectives in, 27–40 reasons for concerns with, 27–29 requirements analysis phase in,
34–35 reviewing data integrity, 85–86 sample, 573–79 specific software for, 206 traditional methods in, 34–36
Database models hierarchical, 5–9 network, 9–12 relational, 12–18
Database oriented business rules, 407
Database server, 20 Database software
as basis for database design, 497–98
programs for, xxxvii–xxxviii Data dictionary, 283 Data integrity, 17, 33, 71–72, 281–82,
323, 481–88 business rules and, 72 field-level, 71 impaired, 503–4 relationship-level, 71 reviewing and refining, 85–86, 483
at the field level, 484 at the level of business rules,
484–85 at the level of views, 485–86 reasons for, 482
at the relationship level, 484 at the table level, 483
table-level, 71 using views in enforcing, 449
Data modeling, 35–36 Data problems, xxxix Data structures, creating, 82–83 Data table, 53, 192 Data types, 294–97
alphanumeric, 296 approximate numeric, 295 bit, 295 character, 294 datetime, 295, 296 exact numeric, 295 extended, 296 interval, 295 national character, 294–95 numeric, 296 reviewing, 142–44
Data usage, reviewing, 142–44 Data view, 449–54
multitable, 451–54 single-table, 449–51
Data warehouse, 23 DateTime data type, 295, 296 DB2, 19 dBase, 19, 124 DBMS software program, 124 Decimal places, 297 Default value, 302–3 Deletion rules
cascade, 382, 384, 386 deny, 382, 384 nullify, 382, 384, 386 restrict, 382, 384, 386 set default, 382, 384, 386–87
Deny deletion rule, 382, 384 Display format, 299–300 Division (÷), 307 Documentation
assembling for database, 486–87 reviewing, for each view, 470–71
Documentation forms, 567–70
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604 Index
Domain integrity, 71 Duplicate fields, 124, 226–27, 228
in flat-file design, 493 resolving unnecessary, 229–35 in spreadsheet design, 494
Duplicate items, resolving, 184–86 Dynamic data, 4
Edit rule, 304 Encapsulation, 22 End-user applications, 34 Entity integrity, 71 Entity-relationship (ER) diagram-
ming, 35 Enumerated list, 168 Exact numeric data type, 295 Explicit information, 113 Extended data types, 296 Extended relational data model, 22 eXtensible Markup Language (XML),
23
Fear factor, 96 Field(s), 13, 36, 55–56, 163, 181, 281
associating with tables, 205–8 calculated, 55, 464–67, 469 compiling a complete list of, 162–77 composite, 55 defining field specifications for,
314–18 duplicate, 124, 226–27, 228 elements of the ideal, 284 grouping, 458 guidelines for composing descrip-
tion of, 291–93, 559 ideal, 213–16, 557–58 multipart, 55, 216–18 multivalued, 55, 219–25, 358–61,
564 non-key, 301 reference, 229 refining, 208–25 resolving multipart, 216–18 resolving multivalued, 219–25
reviewing and refining data integ- rity at level of, 484
single-value, 223 using ideal, to resolve anomalies,
213–16 Field-level integrity, 71, 282, 283–84,
297, 558 Field list
calculated-, 170–71 preliminary, 162–70
Field names, 285 guidelines for creating, 209–12,
560 improving, 208–12
Field specifications, 70, 281–319 anatomy of, 284–308 defining, for each field in the data-
base, 314–18 establishing, 83 general elements in, 70 logical elements in, 70 physical elements in, 70 reasons for importance of, 282–83 using unique, generic, and replica,
308–14 Field specification sheet, 568 Field specific business rules, 409–10,
412–13 defining and establishing, 413–21,
555 File systems, 120–21 Filters, 469 Final table list, 361
defining, 191–205 First-order predicate logic, 30, 31 Flat-file design, 492–93 Foreign keys, 36, 59, 60, 61, 252,
268, 287, 300, 374–81 elements of, 374–81, 556 in establishing one-to-many rela-
tionship, 357–58 in establishing one-to-one relation-
ship, 353–57 FoxPro, 19
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Index 605
Fox Software, 19 Full specifications
general elements in, 285–93 logical elements in, 285, 300–308 physical elements in, 285,
293–300
General elements, 70, 285–93 alias(es), 289–91 description, 291 elements in, 377–78 field names, 285 label, 287 parent table, 287 shared by, 289 source specification, 288 specification type, 287–88
Generic specification, 288, 309 Geographic information systems
(GIS), 21 Grouping field, 458
Hierarchical database model, 5–9 Human-knowledge databases, 121
IBM, 19, 23 IBM Informix Dynamic Server, 22 Ideal field
elements of, 557–58 using, to resolve anomalies,
213–16 Ideal table
elements of, 227–28, 558 using, to refine table structures,
227–35 Implicit information, 113 Implied subjects, 182–84 Inconsistent data, 503 Index, 61 Indexed view, 58, 448 Information, 45–46
explicit, 113 future requirements, 155–57 implicit, 113
inaccurate, 504 reviewing requirements for, 148–57
additional, 152–55, 159–60 current, 149–51, 158–59 future, 155–57, 160––161 overall, 161–62
Information presentation in database analysis, 129–33
reports, 129, 130, 131 screen, 129–31 Web pages, 130, 132–33
Inheritance, 22 Inherited database, 80 Input mask, 299 Integrity. See also Data integrity;
Field-level integrity; Relationship- level integrity; Table-level integrity
domain, 71 entity, 71 multilevel, 17 referential, 7, 71
Integrity-related terms data integrity, 71–72 field specification, 70
Interactive Graphics Retrieval System (INGRES), 19
International Organization for Stan- dardization (ISO), 294
Internet, influence on database use, 23 Interval data type, 295 Interview(s)
asking questions in, 135–36 basic, techniques, 135 conducting, 91–100
in database analysis, 133–42 identifying characteristics in,
138–41 identifying subjects in, 136–38 interviewer guidelines for, 95–100,
562–63 of management, 157–62, 203–5 participant guidelines for, 93–95,
562
From the Library of Stephen Benoit
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606 Index
Interview(s), continued in reviewing initial table structures,
270–77 of users, 142–57, 203–5
Interviewer guidelines, 95–100
Jargon in field specifications, 292
Keyboard characters, 298 Keys, 59–61, 251–79
alternate, 268, 300 candidate, 253–61
artificial, 259–61 composite, 257 elements of, 253–59, 556 surrogate, 259
establishing, for each table, 252–70
foreign, 36, 59, 60, 61, 252, 268, 287, 300, 374–81
elements of, 374–81, 556 in establishing one-to-many
relationship, 357–58 in establishing one-to-one
relationship, 353–57 importance of, 252 non-, 268–69, 300 primary, 36, 52–53, 59, 227–28,
261–68, 300 composite, 266–67, 361 elements of, 262–67, 557 in establishing one-to-many
relationship, 357–58 in establishing one-to-one
relationship, 353–57 field for, 261 rules for establishing, 267–68,
557 Key structure, 300 Key type, 300
Label, 287 Legacy database, 80, 121, 122,
123–25 Length, 297
Letters, 298 Linking tables, 62, 66, 192, 198
in establishing, many-to-many self-referencing relationship, 371–73
in establishing many-to-many relationships, 361–67
Logical child relationship, 8 Logical design, xiii Logical elements, 70, 285, 300–308
comparisons allowed, 305–6 default value, 302–3 edit rule, 304 elements in, 378–79 key structure, 300 key type, 300 null support, 301–2 operations allowed, 306–8 range of values, 303–4 required value, 302 uniqueness, 301 values entered by, 302
Logical relationship, 322 Lookup table, 54, 430 Lotus Freelance Graphics, 130
Mainframe databases, 123–24 Management
business rules in working with, 413
conducting separate interviews for, 96
interviewing, 157–62, 203–5 reviewing field lists with, 171–77 verifying table relationship with,
393 working with views with, 461–62
Mandatory participation, 387–90 Many-to-many relationships, 65–68,
330–32, 349 establishing, 361–67 problems with, 332–37 in relational model, 13 self-referencing, 339–41
establishing, 371–73
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Index 607
Materialized view, 448 Mathematical theory, 31 Microrim, 19 Microsoft, 21
Access, 16, 57, 447 PowerPoint, 130 SQL Server 200, 20–21
Missing values, 48 Mission objectives, 79–80, 182,
563 composing, 110–15 defining, 108–15 using, 189–91 well-written, 108–10
Mission statements, 79–80, 563 composing, 104–6 defining, 101–8 well-written, 102–4
Mulilevel integrity, 17 Multimedia storage systems, 21 Multipart fields, 55
in flat-file design, 493 resolving, 216–18 in spreadsheet design, 494–95
Multiplication (χ), 307 Multitable data view, 451–54 Multivalued fields, 55
resolving, 219–25, 358–61, 564 in spreadsheet design, 495
National character data type, 294–95
Network database model, 9–12 Nodes, 9, 10 Non-key field, 301 Non-keys, 268–69, 300 Normal forms, 36–37 Normalization, 36, 39 Nouns, looking for, in identifying data-
base subjects, 136–38 Nullify deletion rule, 382, 384, 386 Nulls, 47
problem with, 50–52 value of, 48–50
Null support, 301–2
Numbers, 298 Numeric data type, 296
Object Management Group (OMG), 21–22
Object-oriented database, 21 Object-oriented programming
language, 21 Object-relational database, 21, 22 Object-role modeling, 35 One-to-many relationships, 64–65,
327–29, 349 establishing, 357–58 in relational model, 13 self-referencing, 338–39
establishing, 367–71 One-to-one relationships, 63–64,
324–27, 349 establishing, 353–57 in relational model, 13 self-referencing, 338
establishing, 367–71 On-line analytical processing (OLAP)
scenarios, 4 On-line transaction processing (OLTP)
scenarios, 4 Open-ended questions in interviews,
93, 97, 104–5, 110 Operating system software, finetun-
ing, 504 Operational database, 4, 5 Operations allowed, 306–8 Optional participation, 387–90 Oracle9i Application Server, 19, 21 Oracle Corporation, 21 ORDER BY clause, 15, 16 Orphaned records, 382 Ownership-oriented questions, 344
Paper-based database, 80, 120–21, 122, 123
Paradox, 19 Parent/child relationship, 6, 10, 64 Parent table, 287 Participant guidelines, 93–95
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608 Index
Participation degree of, 69–70
business rules and, 411–12 identifying, for each table,
390–93 types of, 68–69
identifying, for each table, 387–90
PC-based legacy database, 124 Physical elements, 70, 285, 293–300
character support, 297–98 data type, 294–97 decimal places, 297 display format, 299–300 input mask, 299 length, 297
Physical implementation, xiiii Prefixes, use of, in tables, 210 Preliminary field list, 182, 205
existence of new characteristics in samples, 166–70
reviewing and refining list of char- acteristics, 162–66
Preliminary table list, defining, 182–91
Primary key(s), 36, 52–53, 59, 227–28, 261–68, 300
composite, 266–67, 361 elements of, 262–67, 557 in establishing one-to-many
relationship, 357–58 in establishing one-to-one
relationship, 353–57 field for, 261 in flat-file design, 493 rules for establishing, 267–68,
557 Primary key value, 261 Processing performance, improving,
502–5
Questions action-oriented, 344 associative, 343
closed, 97 contextual, 344–45 in interview, 135–36 open-ended, 93, 97, 104–5, 110 ownership-oriented, 344 preparing, prior to the interview,
97
Range of values, 303–4 R:BASE, 16, 19 Records, 13, 56–57
orphaned, 382 Recursive relationship, 338 Redundant data, 124, 226, 503 Reference fields, 229 Referential integrity, 7, 71 Relational databases, 3–25, 124
advantages of, 17–18 first-order predicate logic in, 30,
31 history of, 4–12 knowledge and skills necessary to
design, 509 model for, 12–18 set theory in, 30, 31
Relational databases management systems (RDBMS), 18–21, 283
Relations, 13, 52 Relationship-level integrity, 61, 71,
323, 394–400, 564 keys and, 252
Relationship-related terms participation, 68–70 relationships, 62–68
Relationship specific business rules, 410–12
defining and establishing, 421–28, 555–56
Replica specification, 288, 309 Reports, 129 Required value, 302 Requirements analysis, 34–35 Restrict deletion rule, 382, 384,
386
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Index 609
Retrieval of data, 15–16 Rules. See also Business rules
bending or breaking, 501–7
Samples, reviewing, in interview, 144–48 Saved queries, 57, 447 Screen presentations, 129–30 SELECT...FROM statement, 15–16 SELECT statement, 45 Self-interviews, 92 Self-referencing relationships, 337–41
establishing, 367–73 many-to-many, 339–41 one-to-many, 338–39 one-to-one, 338 participation and, 389
Semantic-object modeling, 35 Set default deletion rule, 382, 384,
386–87 Set structures, 9, 10 Set theory, 30, 31 Single-table data view, 449–51 Single-value field, 223 Slide shows, 129 Social Security number, candidate or
primary key, 256 Source specification, 288 Special characters, 298 Specification type, 287–88 Spreadsheet design, 493–97 Spreadsheet view mind-set, 495–97 SQL. See Structured Query Language
(SQL) SQL/3, 294 SQL/92, 294 SQL Queries for Mere Mortals, 16 Static data, 4 Structured Query Language (SQL), 15,
47, 294 components of basic query in, 15–16
Structure-related terms field, 55–56 index, 61 keys, 59–61
record, 56–57 table, 52–54 view, 57–59
Subjects identifying
implied, 182–84 in interview, 136–41 technique for, 141, 160
subordinate, 236 using the list of, 184–89
Subordinate subjects, 236 Subset tables, 193, 326
establishing, 235–47 Subtraction (-), 307 Surrogate candidate key, 259 System R, 19
Table(s), 13, 52–54, 82 associating with fields, 205–8 associative, 62 base, 57, 447, 469 data, 53, 192 degree of participation, 69–70 elements of ideal, 374 establishing keys for, 252–70 establishing subset, 235–47 ideal, 227–35, 558 identifying the degree of participa-
tion for, 390–93 identifying type of participation for,
387–90 linking, 62, 66, 192, 198, 361–67,
371–73 lookup, 54, 430 parent, 287 reviewing and refining data integ-
rity at level of, 483 subset, 193, 235–47, 326 types of participation, 68–69 validation, 54, 198, 428–34, 459 virtual, 447
Table description, 191 guidelines for composing, 199–203,
559
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610 Index
Table-level integrity, 71, 269–70, 282, 565
keys and, 252 Table list
defining final, 191–205 defining preliminary, 182–91
Table names, guidelines for creating, 193–98, 560–61
Table relationships, 62–63, 321–401 defining a deletion rule for each,
381–87 determining and establishing,
83–84 establishing characteristics for,
381–84 establishing each, 353–74 identifying, 561 identifying existing, 341–53 identifying the degree of participa-
tion for each table, 390–93 identifying the type of participation
for each table, 387–90 importance of, 322–23 keys in establishing, 252 many-to-many, 65–68, 330–32, 349
establishing, 361–67 problems with, 332–37 in relational model, 13 self-referencing, 339–41
establishing, 371–73 one-to-many, 64–65, 327–29, 349
establishing, 357–58 in relational model, 13 self-referencing, 338–39
establishing, 367–71 one-to-one, 63–64, 324–27, 349
establishing, 353–57 in relational model, 13 self-referencing, 338
establishing, 367–71 relationship-level integrity and,
394–400 reviewing and refining data integ-
rity at level of, 484
self-referencing, 62–63, 337–341 establishing, 367–73
types of, 63–68, 323–41 verifying, with users and manage-
ment, 393 Table structures, 181–249
associating fields with each table, 205–8
defining the final table list, 191–205 defining the preliminary table list,
182–91 refining, 226–47 refining the fields, 208–25 reviewing the initial, 270–77
Table types, 191, 192 indicating, 198–99
Terminology importance of, 44–45 integrity-related, 70–72 relationship-related, 62–70 structure-related, 52–61 value-related, 45–52
Theory, importance of, 29–31 Tuples, 13, 52, 56
Unbiased viewpoint, 182–83 UniData, 21 Uniqueness, 301 Unique specification, 287, 309 Unknown values, 49 Users
accessing data within a network database, 11
business rules in working with, 413
conducting seperate interviews for, 96
interviewing, 142–57, 203–5 reviewing data type and usage,
142–44 reviewing information require-
ments, 148–57 reviewing the samples, 144–48
reviewing field lists with, 171–77
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Index 611
verifying table relationship with, 393
working with views with, 461–62
Validation, 193 Validation tables, 54, 198, 428–34,
459 defined, 430 using, to support business rules,
431–34 Validation views, 58, 458–60
using views in enforcing, 449 Value lists, 168–70 Value-related terms
data, 45 information, 45–46 null, 47–52
Values entered by, 302 Versant Corporation, 21 Versant ODBMS, 21 View(s), 57–59, 447–78
aggregate, 454–58 base table of, 447 data, 449–54 defined, 447
determining and defining, 85, 460–76
identifying requirements, 561–62 indexed, 58, 448 materialized, 448 multitable data, 451–54 reasons for defining and using in
database, 448–49 reviewing and refining data integ-
rity at level of, 485–86 reviewing the documentation for,
470–71 single-table data, 449–51 validation, 58, 458–60
Viewpoint, unbiased, 182–83 View Specifications sheet, 470–71,
570 recording views on, 469–70
Virtual table, 447
Web pages, 130, 132–33 WHERE clause, 15, 16
Zero, 47 Zero-length string, 47
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UNDERSTANDING NORMALIZATION
Understanding Normalization BC-1 Copyright © 2001-2003 Michael J. Hernandez, All Rights Reserved
A solid database structure is the foundation of any successful database application, and you will inevitably encounter problems if your database is poorly designed. Regardless of how you access your data, the information you retrieve is only as good as the data upon which it is based. In this paper, I’ll cover a traditional database design topic that seems to be quite a hurdle for many database designers and developers: Normalization. Normalization is the process of refining table structures into a proper state so that they can store data as efficiently as possible. Here you'll discover why Normalization is crucial and learn how to normalize your tables using Normal Forms. First, you'll learn about modification anomalies and Dependency Theory—two issues crucial to understanding Normal Forms. Then, I’ll discuss each Normal Form in detail and you'll learn how they resolve problems such as multivalued dependencies, transitive dependencies, and poor data integrity.
The Normalization Process One of the most challenging aspects of traditional database design is Normalization. Much has been written about it, many people have struggled with it, and some have actually understood it. Yet, despite its reputation as a difficult process to learn and implement, it's actually pretty easy once you understand three fundamental concepts:
1. The overall premise behind Normalization
2. Modification anomalies
3. Data dependencies
If you learn about these concepts first, you'll find it easier to grasp the theories behind each of the Normal Forms. We'll start by defining Normalization.
What is Normalization? It is the process of decomposing large, inefficiently structured tables into smaller, more efficiently structured tables without losing any data in the process. Normalization supports the proposition that a well-defined database contains no duplicate data and keeps redundant data to an absolute minimum. This, in turn, guarantees data integrity and ensures that the information retrieved from the database will be accurate and reliable. Figure 1 illustrates the Normalization process.
Normalization Process
Non-Normalized Tables
Ideal Structures
Figure 1. A graphical representation of the Normalization process
Decomposing improperly structured tables is not an arbitrary process. It is instead a methodical process you perform by testing each table against a set of Normal Forms.
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Understanding Normalization BC-2 Copyright © 2001-2003 Michael J. Hernandez, All Rights Reserved
A Normal Form is an algorithm you use to test the structure of a table. It helps to eliminate possible table or field anomalies and to ensure efficient table and field structures. There are seven Normal Forms, and each one was created to deal with specific types of problems. Here are the names of the Normal Forms, including the general issue upon which each is based:
• First Normal Form Based on Functional Dependency
• Second Normal Form Based on Functional Dependency
• Third Normal Form Based on Functional Dependency
• Fourth Normal Form Based on Multivalued Dependency
• Fifth Normal Form Based on Join Dependency
• Boyce/Codd Normal Form Based on Functional Dependency
• Domain/Key Normal Form Based on the definition of Domains and Keys
Now that you have a basic idea of what the Normalization process is about, lets move on to the second fundamental concept: modification anomalies.
Modification Anomalies We've just discussed the concept behind the Normalization process, but we didn't discuss why you should even go through the process in the first place. (You would have thought I'd mention it before this moment, but you'll soon see why it makes more sense to discuss it here.)
The main reason you put your tables through the Normalization process is to ensure sound, efficient table structures. Improperly designed tables typically exhibit poor data integrity and are subject to modification anomalies and data dependency problems. If you fail to address these problems, you'll find that the information you retrieve from the database will be inconsistent, inaccurate, and in some extreme cases, totally invalid.
In order to understand why you might consider a table to be improperly designed, you must understand the problems it exhibits. (And rather obscurely, as you might think at the moment.) We'll begin by discussing modification anomalies.
A constraint placed upon the ability to modify data in a table that is imposed by the table's structure is known as a modification anomaly. There are three types of modification anomalies that a table can exhibit: Insert, Delete, and Update.
Insert Anomaly
An Insert anomaly exists in a table when there is an unnecessary or unreasonable constraint placed upon the task of adding a new record, or when adding a new record will cause unnecessary or unreasonable data redundancy. Figure 2-a illustrates an example of the first type of Insert anomaly. Because data on employees and departments is being stored in the same table, you cannot enter data for a new department until you have at least one employee assigned to the department. Conversely, you cannot add a new employee unless you're ready to assign him or her to a particular department. This type of anomaly can be hard to spot at first glance because it is somewhat subtle.
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EmployeesAndDepartments
Figure 2-a. Example of an Insert anomaly imposing an unnecessary constraint.
The second type of Insert anomaly, shown in Figure 2-b, is easier to spot because of the redundant data in the table. In this case, all of the data for a given customer must be repeated when another sales representative is assigned to that customer. This is borne out in the records for Kenneth Peacock.
SalesRepAccounts
Figure 2-b. Example of an Insert anomaly causing redundant data.
Delete Anomaly
A Delete anomaly exists when deleting a record would remove data not intended for deletion. Figure 3-a shows the table used in Figure 2-a to illustrate an Insert anomaly. The same premise holds—data on both employees and departments is being stored in the table. However, this table also has a Delete anomaly that is just the flip side of the Insert anomaly. In this case, it is possible to delete the only data you have for a particular department if you delete the wrong employee. Such is the case with the "Information Services" department; if you delete the record for John Callahan, you'll also delete the only data you have on that department.
EmployeesAndDepartments
Figure 3-a. Example of a Delete anomaly affecting a single record.
Figure 3-b shows a table that stores data on both sales representatives and orders. This table also has a Delete anomaly, but the results of deleting a record are more serious. By deleting a sales representative, it is possible to delete a large number of records. Deleting Mike Hernandez, for example, will also delete data on orders 2, 4, and 5!
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SalesRepOrders
Figure 3-b. Example of a Delete anomaly affecting multiple records.
Update Anomaly
An Update anomaly exists when modifying a specific value necessitates the same modification in other records or tables. In Figure 4, you would have to make changes to three records if Lone Star Distributors decided to change its name. On the surface, this doesn't seem like a big deal. However, it is a significant problem when you're dealing with a large number of records. You could write programming code to deal with the problem, but then you're writing code that you really shouldn't have to write in the first place. "But I could just update the data using an SQL statement," you say. Unfortunately, that will work only if all the entries are spelled exactly the same.
CustomerOrders
Figure 4. Example of an Update anomaly imposing unnecessary modifications.
You've probably figured out by now that you want to do everything possible to avoid modification anomalies. You can and will avoid these anomalies by putting each of your tables through the Normalization process.
Let's now take a look at the third and final fundamental concept: dependencies.
Dependencies: The Good, the Bad, and the Ugly The notion of dependencies (and modification anomalies, for that matter) falls under the umbrella of Dependency Theory. Dependency Theoryis the field of study comprising Normalization Theory, dependency principles, and other related topics. You learned earlier that most Normal Forms are based on various types of dependencies, and it is for this reason that you must study them. Once you understand dependencies in general, Normal Forms are much easier to learn and understand.
Note This is by no means an exhaustive study of dependencies. The idea here is to provide you with a solid idea of what dependencies are about and how they fit into Normalization.
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Understanding Normalization BC-5 Copyright © 2001-2003 Michael J. Hernandez, All Rights Reserved
There are four types of dependencies we'll discuss in this section: functional dependencies, transitive dependencies, multivalued dependencies, and join dependencies.
Functional Dependency—the Good
A functional dependency (FD) exists between two fields, A and B, when a distinct value of A is directly associated with a distinct value of B. Given a value in A for a specific record in a table, you can always retrieve the associated value in B for that record.
A FD is diagrammed as A→→→→B and can be read equivalently as either of the following statements:
The value of A determines the value of B.
The value of B is functionally dependent on the value of A.
Note In any dependency diagram you encounter, the field on the left-hand side is called the determinant and the field on the right-hand side is called the dependent.
Properly designed tables always contain well-defined functional dependencies. An excellent example of a functional dependency is a primary key. The primary key functionally determines all non-key fields in the table—given a primary key value for a specific record in a table, you can retrieve the values of the remaining non-key fields in that record. (This is true of candidate keys as well. But, as you know, only one candidate key will serve as the primary key of the table.)
Figure 5 illustrates this example quite well. In this case, CustomerID determines the values of the other fields in the table.
Customers
Figure 5. Example of a functional dependency.
Transitive Dependency—the Bad
Assume three fields, A, B and C, have the following functional dependencies:
A→→→→B
B→→→→C
A transitive dependency (TD) exists between A and C because a distinct value of A is indirectly associated with distinct value of C by way of B. Here's the logic behind this statement:
A determines the value of B.
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Understanding Normalization BC-6 Copyright © 2001-2003 Michael J. Hernandez, All Rights Reserved
B determines the value of C.
Therefore, A transitively determines the value of C.
A TD is diagrammed as A⇒⇒⇒⇒C and can be read equivalently as either of the following statements.
The value of A transitively determines the value of C (via B).
The value of C is transitively dependent on the value of A (via B).
As you know, a properly designed table represents one, and only one, subject. However, a table that contains transitive dependencies will describe two or more subjects, depending on the number of transitive dependencies present. (For example, a table with one transitive dependency will describe two subjects, and a table with two transitive dependencies will describe three subjects.) A table in this state is improperly designed and is subject to modification anomalies.
Figure 6 shows an Employee table with a transitive dependency between the EmployeeID and Department fields. Here's the logic:
EmployeeID determines the value of DepartmentID.
DepartmentID determines the value of Department.
Therefore, EmployeeID transitively determines the value of Department.
Employees
Figure 6. Example of transitive dependency.
Based on what you've just learned, you can see that the transitive dependency causes the table to describe two distinct subjects: employees and departments. You'll have to put the table through the Normalization process to remove the transitive dependency and keep the table free from all modification anomalies.
Multivalued Dependency—the Ugly
A multivalued dependency (MVD) exists between two fields, A and B, when a distinct value of A is directly associated with two or more values of B.
An MVD is diagrammed as A→→→→→→→→B and can be read equivalently as either of the following statements:
The value of A determines multiple values of B.
Multiple values of B are functionally dependent on the value of A.
A multivalued dependency can exist at the field level or the record level, and two or more distinct, independent multivalued dependencies can appear in a table simultaneously.
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Understanding Normalization BC-7 Copyright © 2001-2003 Michael J. Hernandez, All Rights Reserved
Multivalued dependencies are similar to transitive dependencies in that their presence in a table indicates that the table describes two or more subjects. Not surprisingly, a table in this state is improperly designed and is subject to modification anomalies.
Figure 7-a shows a table with a field-level multivalued dependency. The transitive dependency exists between the EmployeeID and Committees fields—a single EmployeeID value is associated with one or more Committee values. Although it's not obvious at this point, the table does describe two subjects: Employees and CommitteeMembers.
EmployeeCommittees
Figure 7-a. Example of a field-level multivalued dependency.
The table in Figure 7-b shows a multivalued dependency at the record-level that exists once again between EmployeeID and Committee. In this case, however, the employee data is repeated for each committee in which the employee participates. And this table, like its counterpart in the previous example, also describes the same two subjects: Employees and CommitteeMembers.
EmployeeCommittees
Figure 7-b. Example of a record-level multivalued dependency.
Figure 7-c shows an example of a table with two independent multivalued dependencies. One multivalued dependency exists between EmployeeID and Language, and the other exists between EmployeeID and DeveloperCertification. Note how the employee data is repeated for every language spoken or certification acquired. For example, if Ann Patterson obtains a Visual Studio certification, you'll have to enter yet another record for her in the table.
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Understanding Normalization BC-8 Copyright © 2001-2003 Michael J. Hernandez, All Rights Reserved
These multivalued dependencies are called "independent" because one has absolutely nothing to do with the other. Speaking Spanish is not a requirement for being a Visual InterDev developer, and being a SQL Server developer is not a requirement for speaking German. As you've probably already determined, this table describes three subjects because of the two multivalued dependencies: Employees, EmployeeLanguages, and EmployeeCertifications.
EmployeeInformation
Figure 7-c. Example of two independent multivalued dependencies.
Regardless of the type, all multivalued dependencies must be resolved by Normalization so that the table will be free of any modification anomalies
Join Dependency—the Odd Couple
A join dependency (JD) exists in table A if every record in the table can be reconstructed by an SQL JOIN operation that reunites all tables created by its decomposition. This must hold true for all records existing in table A at the time of its decomposition and for any valid record that could have been entered prior to its decomposition. (Records added to the decomposed tables must be able to form a valid record for table A when they are united via the JOIN.) Additionally, no records should be lost and no spurious records should be added.
You could say that the table in Figure 8-a has a join dependency because you can decompose it into smaller tables. (Just because you can decompose a table further doesn't necessarily mean you should.) For example, let's say that you wanted to keep sensitive information, such as a vendor's discount or status, from being accessed by everyone in the office. You could decompose this table into two smaller tables (VendorStatus and VendorInformation, respectively) as Figure 8-b shows.
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Understanding Normalization BC-9 Copyright © 2001-2003 Michael J. Hernandez, All Rights Reserved
Vendors
Figure 8-a. Example of a table with a join dependency.
VendorStatus
VendorInformation
Figure 8-b. The result of decomposing the Vendors table.
Because of the join dependency, you should be able to execute the following SQL statement and recreate the original Vendors table. Also, you should not lose any data or gain any bogus records in the process.
SELECT VendorInformation.VendorID, VendName, Discount, Status, VendCity, VendPhoneNumber, VendWebPage
FROM VendorInformation INNER JOIN VendorStatus
ON VendorInformation.VendorID = VendorStatus.VendorID
This SQL statement will, in fact, recreate the original Vendors table without any problem.
There is no requirement stating that every table must contain a join dependency. In fact, the only tables that are candidates for join dependencies are those that can be further decomposed into smaller tables. Once the decomposition has taken place, the rules stated above must hold for the join dependency to be valid. Otherwise, you'll have to
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take the table through the Normalization process to determine whether it should indeed contain a join dependency.
Well, we've covered all of the fundamental concepts you need to know before tackling Normal Forms. So let's get down to business and move to our discussion on Normal Forms.
Understanding Normal Forms
Before You Begin …
So, you've identified your tables and populated them with the fields you believe are most appropriate at this time, and you've even gone so far as to identify relationships between some of the tables. Now you're ready to take them through the Normalization process. Or are you?
There are a couple of things you need to check before you start the Normalization process.
1. Each table must have a primary key.
2. A table cannot contain repeating groups of data.
Each of your tables must be in this state in order for the Normalization process to be effective. Otherwise, you could run into problems that might easily have been avoided.
Figure 9 shows a non-normalized Orders table. Although it's in a sad state at the moment, it is ready for the Normalization process. It does have a primary key, and it doesn't contain repeating groups of data, per se. (As you can see, there are repeating groups of values within the Items field.)
However, the Items field has two obvious problems: It is a multipart field and a multivalued field. It's a multipart field because its value can be broken down into smaller, more distinct parts. It's a multivalued field because a single OrderID value can be associated with one or more values within the Items field. (This is a field-level multivalued dependency, isn't it?)
Orders
Figure 9. A non-normalized Orders table.
Because the table is in an acceptable state, you'll take it through the Normalization process. (We'll actually work with a few different tables throughout this discussion, but we'll start with this one first.)
Let's begin at the beginning: First Normal Form (1NF).
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Understanding Normalization BC-11 Copyright © 2001-2003 Michael J. Hernandez, All Rights Reserved
Note: As we examine each Normal Form, I'll start with its technical definition and then provide a layman's explanation and example.
The Normal Form definitions I use here are taken from C. J. Date’s An Introduction to Database Systems, 7th Edition (Addison Wesley, 2000).
The term relvar (for relational variable) represents the term table for our purposes.
First Normal Form
A relvar is in 1NF if and only if in every legal value of that relvar, every tuple contains exactly one value for each attribute.
The purpose of this Normal Form is to ensure that a table does not contain any multipart or multivalued fields and that each field holds only a single value for any given record.
You can begin to normalize the Orders table by removing the multivalued characteristics of the Items field.
Orders
Figure 10-a. Beginning to apply .
The result is that you now have a repeating group of fields: Item1, Quant1, Price1, Item2, Quant2, Price2, etc. (see Figure 10-a). You take care of this problem by consolidating them into three distinct fields: Item, Quantity, and Price. Additionally, you should remove the multipart characteristics of the Item field by dividing it into two distinct fields: ProductID and Product. Figure 10-b shows the results of these modifications.
Orders
Figure 10-b. The Orders table in 1NF.
Although the table is far from perfect, it is now in 1NF and is ready to be tested against Second Normal Form (2NF).
Second Normal Form
A relvar is in 2NF if and only if it is in 1NF and every non-key attribute is irreducibly dependent on the primary key.
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Your table should already be in 1NF before you reach this point; 2NF then ensures that each non-key field in the table is functionally dependent upon the primary key and that the table does not contain calculated fields.
You can readily see that the Orders table does not conform to 2NF because it has three distinct problems:
1. It actually describes two subjects: Orders and OrderDetails.
2. It contains a calculated field (Total).
3. It contains a transitive dependency between OrderID and Product.
Your first order of business is to decompose the table into two smaller tables called Orders and OrderDetails (see Figure 11-a). This ensures that the Orders table describes a one and only one subject.
Orders
OrderDetails
Figure 11-a. Applying 2NF to the Orders table.
The newly revised Orders table is now in 2NF, so you can turn your attention to the OrderDetails table.
Note that the transitive dependency and calculated field have migrated to this table during the decomposition process. Dealing with the calculated field is not a problem because all you have to do is remove it from the table; the transitive dependency is another matter. You learned earlier that the presence of a transitive dependency indicates that the table describes two subjects. In this case, the table actually describes OrderDetails and Products. You resolve the transitive dependency by removing the Product field from the OrderDetails table and then creating a new Products table with ProductID and Products as its fields. It is important that you use the ProductID field as part of the new Products table because it is what will relate the Products table to the OrderDetails table. Once you're finished, the OrderDetails table is in 2NF.
Figure 11-b shows the newly revised OrderDetails table and the new Products table. Pop quiz: Is the new Products table in at least 2NF?
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OrderDetails
Products
Figure 11-b. The OrderDetails and Products tables in 2NF.
With the OrderDetails table in 2NF, you can now move on to Third Normal Form (3NF).
Third Normal Form
A relvar is in 3NF if and only if it is in 2NF and every non-key attribute is nontransitively dependent on the primary key.
As the definition states, a table must already be in 2NF before you can apply 3NF. If this is the case, you then apply 3NF to ensure that the table has the following characteristics:
• Each field value is independently updateable; changing the value for one field in a given record does not adversely affect the value of any other field in that record.
• Each field identifies a specific characteristic of the table's subject.
• Each non-key field in the table is functionally dependent upon the entire primary key
• The table describes one and only one subject.
Because the Orders and OrdersDetail tables are already in 2NF, you can now apply 3NF to both tables.
When you apply 3NF to the Orders table, you end up with the structure shown in Figure 12-a. Notice anything different about this structure and its 2NF counterpart in Figure 11- a?
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Orders
Figure 12-a. The Orders table in 3NF.
If your answer is no, then you're absolutely correct. It just so happens that the Orders table already conforms to 3NF, so you don't need to make any modifications to its structure.
If you take a look at the OrderDetails table back in Figure 11-b, you'll see that it has one minor problem: One of its fields does not describe the table's subject. Can you determine which field is the culprit? Here's a hint: The field in question is involved in a transitive dependency.
The offending field is the Price field. Price doesn't represent a specific characteristic of an order detail as much as it describes a specific characteristic of a particular product. Additionally, its value is actually determined by ProductID. If you consider that the OrderDetails table has a composite primary key consisting of OrderID and ProductID, you can see that the value of Price is not dependent on the entire primary key, as required by 3NF. You can solve this dilemma by removing Price from the table. (You won't lose anything in the process because Price is already in the Products table.) Figure 12-b shows the result of your modification.
OrderDetails
Figure 12-b. The OrderDetails table in 3NF.
Let's now take a look at a slightly different way of arriving at the same structure by using Boyce/Codd Normal Form.
Boyce/Codd Normal Form
A relation is in Boyce/Codd Normal Form if and only if the only determinants are candidate keys.
Boyce/Codd Normal Form is a different version of 3NF and, indeed, was meant to replace it. The purpose of Boyce/Codd Normal Form is twofold:
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Understanding Normalization BC-15 Copyright © 2001-2003 Michael J. Hernandez, All Rights Reserved
1. It ensures that a field that determines the value of any or all non-key fields in a table is be a candidate key for that table.
2. It ensures that a table describes one and only one subject. (This is implied by enforcing candidate keys.)
Boyce/Codd Normal Form is slightly stronger than 3NF in that it deals with the possibility of a table having more than one field that could act as the primary key. Provided that you can identify all the valid candidate keys in a table, you can ensure that the table is free of transitive dependencies, and by extension, of modification anomalies.
Note Review time! A candidate key is a field or group of fields that has all the required characteristics of a primary key, the most important of which is that it determines the values of all non-key fields in the table. After you identify the candidate keys for a given table, you select one that will serve as the table's official primary key.
Figure 13-a shows an OrderDetails table with three determinants: OrderID and LineItemNumber (taken as a single unit), OrderID and ProductID (taken as a single unit), and ProductID. In order to apply Boyce/Codd Normal Form, you first need to identify whether these determinants are candidate keys of the table. Would you say that all three are candidate keys?
OrderDetails
Figure 13-a. An OrderDetails table containing three determinants.
You are correct if you answered no—OrderID\ProductID and OrderID\LineItemNumber are the only candidate keys. Although ProductID is not a candidate key, it does determine the value of Product and Price. As you may have already guessed, this means that the Product and Price fields are involved in transitive dependencies with both candidate keys. You will, therefore, have to remove the Product and Price fields from the table. You'll also have to remove the Total field because neither of the candidate keys determines its value. Instead, Quantity and Price determine the value of the Total field. Once you remove these three fields, the table will be in Boyce/Codd Normal Form. Figure 13-b shows the results of your modifications.
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OrderDetails
Figure 13-b. The OrderDetails table in Boyce/Codd Normal Form.
Most tables that are in Boyce/Codd Normal Form will require no further Normalization. However, you'll need to take the table through Fourth Normal Form (4NF) if it contains any multivalued dependencies.
Fourth Normal Form
Relvar Ris in 4NF if and only if, whenever there exist subsets A and Bof the attributes of R such that the (nontrivial) MVD A→→B is satisfied, then all attributes of R are also functionally dependent on A.
The purpose of 4NF is to ensure that a table does not contain any multivalued dependencies and that it describes one and only one subject. (Have you noticed by now that the latter point is a recurring theme across the higher Normal Forms?)
You learned earlier that a table containing multivalued dependencies describes two or more subjects, depending on the number of multivalued dependencies present. You also learned that you must remove all multivalued dependencies from the table. You'll accomplish this by applying 4NF to the table.
Figure 14-a shows a table called EmployeeCommittees that contains a single multivalued dependency. The first version has a field-level multivalued dependency, and the second version contains a record-level multivalued dependency. The manner in which you apply 4NF to each table is exactly the same and yields the same results.
EmployeeCommittees—Version 1
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EmployeeCommittees—Version 2
Figure 14-a. Two versions of the EmployeeCommittees table.
In applying 4NF to a table containing a single multivalued dependency, you build a new table using a copy of the primary key and the field containing the multiple values. Using the primary key as part of the structure of the new table is important because it relates the new table to the original table. (Be sure to give the new table an appropriate name.) You then decompose the original table by removing the multivalued field. And voila! Both the newly revised table and the new table are now in 4NF.
Figure 14-b shows the results of applying these steps to the EmployeeCommittes table.
EmployeeCommittees
Employees
Figure 14-b. The Employees and EmployeeCommittees tables in 4NF.
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Understanding Normalization BC-18 Copyright © 2001-2003 Michael J. Hernandez, All Rights Reserved
If you encounter a table with two or more multivalued dependencies, you just repeat the same steps for each dependency. For example, Figure 14-c shows an employees table with two independent multivalued dependencies.
EmployeeInformation
Figure 14-c. An Employees table with two independent multivalued dependencies.
You'll deal with each multivalued dependency as you did in the previous example.
1. Create a new table using the primary key (EmployeeID) and the first multivalued field (Language). Give the new table an appropriate name.
2. Create another new table using the primary key (EmployeeID) and the second multivalued field (DeveloperCertification). Give the new table an appropriate name.
3. Remove the two multivalued fields from the original table.
The newly revised original table (EmployeeInformation) and the two new tables are now in 4NF. Figure 14-d shows the results of applying 4NF to the EmployeeInformation table.
EmployeeInformation
EmployeeLanguages EmployeeCertifications
Figure 14-d. The EmployeeInformation, EmployeeLanguages, and EmployeeCertifications tables in 4NF.
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Understanding Normalization BC-19 Copyright © 2001-2003 Michael J. Hernandez, All Rights Reserved
Fifth Normal Form
A relvar R is in Fifth Normal Form (5NF)—also called Projection/Join Normal Form (PJ/NF)—if and only if every nontrivial join dependency that holds for R is implied by the candidate keys of R.
You learned earlier in this discussion that a join dependency exists for a given table if the table and all of its original records can be reconstructed by an SQL JOIN operation that reunites all tables created by its decomposition. You can test for this type of dependency by using 5NF.
By the time a table has achieved 4NF, it should be free of all transitive and multivalued dependencies. In most cases, you shouldn't need to decompose the table any further. However, if you suspect that you can (or should) decompose the table once more, you must test whether there is a valid join dependency in the table. There are three key questions that you must answer before decomposing the table any further:
1. Can I create the new table(s) using the primary key or a candidate key as part of the new table structure? (Remember that this was a requirement for resolving transitive and multivalued dependencies.)
2. Can I recreate the original table by using an SQL JOIN operation that reunites all of the tables recreated by the decomposition?
3. Will I lose any records in the process of decomposing the table?
If the answer to each question is yes, then the table is in 5NF, and you can confidently make the decomposition. However, just because you can decompose the table further doesn't necessarily mean that you should.
Figure 15-a shows an Employees table that could possibly be decomposed into smaller tables. Is it in 5NF? Study the table for a moment and use the three questions stated above to make your determination.
Employees
Figure 15-a. Is this table in 5NF?
The answer is yes. You can use the primary key (EmployeeID) or the candidate key (SocialSecurityNumber) as part of a new table structure; you can recreate the original table; and you won't lose any records in the decomposition process.
Why might you possibly want to decompose this table? One possible reason is that you want to separate sensitive employee data from general employee data. For example, you could decompose the original table into the two new tables shown in Figure 15-b.
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Understanding Normalization BC-20 Copyright © 2001-2003 Michael J. Hernandez, All Rights Reserved
EmployeeInformation
EmployeeConfidential
Figure 15-b. New EmployeeInformation and EmployeeConfidential tables.
From the Library of Stephen Benoit
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Understanding Normalization BC-21 Copyright © 2001-2003 Michael J. Hernandez, All Rights Reserved
When you want to see the information from the original table, you can use this SQL statement to do so:
SELECT EmployeeInformation.EmployeeID, SocialSecurityNumber, EmpFirstName, EmpLastName, EmpCity, EmpState, EmpPhoneNumber, MotherMaidenName, BirthDate
FROM EmployeeInformation INNER JOIN EmployeesConfidential
ON EmployeeInformation.EmployeeID = EmployeesConfidential.EmployeeID
You won't often run into situations where you need 5NF, but it's good to know that it's available when you need it.
Domain/Key Normal Form
Relvar Ris said to be in Domain/Key Normal Form (DKNF) if and only if every constraint on R is a logical consequence of the domain constraints and key constraints that apply to R.
DKNF is a newer Normal Form (as Normal Forms go) and is similar to Boyce/Codd Normal Form in that it is partially based on the enforcement of primary keys and candidate keys. So you already understand at least that much of this Normal Form.
But it is also based upon the idea of Domains. Most texts on database design state that a Domain is merely a set of acceptable values from which a specific field can draw its own values. That's only partially true; a Domain is much more than that. A Domain has two sides: a logical side and a physical side. The logical side deals with issues such as default values, range of values, whether the value is required, and whether the value can be null. The physical side deals with issues such as data type, length, decimal places, and allowable characters. Once you understand this idea, you can use this Normal Form.
In order for a table to be in DKNF, it must fulfill these requirements:
1. Each field must be fully and properly defined.
2. Each field must represent a characteristic of the table's subject.
3. Each non-key field in the table must be functionally dependent upon the entire primary key.
4. Each table should represent only a single subject. (Sound familiar?)
A table in DKNF will be free of transitive dependencies, multivalued dependencies, and modification anomalies. In fact, a table in DKNF is automatically in 5NF.
Figure 16-a shows an Employees table that might be a candidate for DKNF. Can you normalize this table further by applying DKNF?
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Understanding Normalization BC-22 Copyright © 2001-2003 Michael J. Hernandez, All Rights Reserved
Employees
Figure 16-a. Can you normalize this Employees table any further?
You can indeed. One of the requirements of DKNF is that the primary key determines the value every non-key column in the table. This certainly isn't the case with the Department field. You'll have to remove the Department field in order to place the table in DKNF. Figure 16-b shows the result of your modification.
Employees
Figure 16-b. The Employees table in DKNF.
Using DKNF depends as much on intuition as anything else. You have to understand the concepts of Keysand Domains thoroughly before you can really benefit from this Normal Form. But it works pretty well once you get the hang of it.
Denormalization Now we tackle one of the most oft' asked questions: What about Denormalization? The real answer is this: Ask a dozen database developers and you'll get a dozen opinions.
Many people who denormalize their database structures do so for “performance reasons”. Here are some of the problems they claim to encounter:
• Queries run slowly.
• Reports take too long to print.
• On-screen forms take time to populate.
• Web pages take too long to populate.
Speed and performance are really relative to a user's definition of the terms. What some people may consider painfully slow may be as fast as greased lightning for others. You should always take performance complaints with a grain of salt and try to take the time to investigate the true nature of a perceived problem.
From the Library of Stephen Benoit
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Understanding Normalization BC-23 Copyright © 2001-2003 Michael J. Hernandez, All Rights Reserved
Although you could justify some Denormalization from a strictly pragmatic sense, you should always denormalize as a last resort. Instead, try some of the following remedies before you embark upon any Denormalization:
• Update your computer equipment. Prices are really low and you can purchase a powerful system quite inexpensively.
• Optimize the operating environment. Do what you can to optimize your network by working closely with your network administrator.
• Optimize the RDBMS program. Make certain you're loading only those pieces of the software that you really need, and carefully tweak any options and settings that are available to you.
• Use indexes effectively. Indexes can speed up query processing enormously, so using them judiciously can have a very positive effect on the time it takes to retrieve information from your database.
• Write good, tight procedural code. Make certain that you're using optimal code structures and that your code offers that path of least resistance to your data.
• Write well-structured SQL statements. Although there are several ways to pose the same query, some statements are optimized better than others. Be sure to check your database documentation for more information on this subject.
• START WITH A NORMALIZED STRUCTURE! 'Nuff said.
The most important point for you to remember is that you will always reintroduce data integrity problems when you denormalize your structures! This means that it becomes incumbent upon you or the user to deal with this issue. Either way, it imposes an unnecessary burden upon the both of you. Denormalization is one issue that you'll have to weigh and decide for yourself whether the perceived benefits are worth the extra effort it will take to maintain the database properly.
A Final Thought In all the years that I've been involved in the database management profession, I've learned that database design is as much an art as it is a science. You learn the science of database design through instruction and training and the art of database design through personal experience. You'll find that studying database theory, design and technology is an on-going exercise and a rewarding experience.
This job never gets boring!
From the Library of Stephen Benoit
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SQL Queries for Mere Mortals A Hands-On Guide to Data Manipulation in SQL Michael J. Hernandez, John L. Viescas
If you are accessing corporate information from the Internet or from an internal network, you are probably using SQL. SQL Queries for Mere Mortals will help new users learn the foundations of SQL queries, and will prove to be an essential reference guide for intermediate and ad- vanced users. The accompanying CD contains five sample databases used for the example queries throughout the book, plus an evaluation copy of Microsoft SQL Server version 7.
0-201-43336-2 • Paperback with CD-ROM • 528 pages • © 2000
The Practical SQL Handbook, Fourth Edition Using SQL Variants Judith S. Bowman, Sandra L. Emerson, Marcy Darnovsky
This latest edition of the best-selling implementation guide to the Structured Query Language teaches SQL fundamentals while providing practical solutions for critical business applications. The Practical SQL Handbook, Fourth Edition now includes expanded platform SQL cover- age and extensive real-world examples based on feedback from actual SQL users. This book begins with a step-by-step introduction to SQL basics and examines the issues involved in designing SQL-based database applications. It fully explores SQL’s most popular implementations from industry leaders, Oracle, Microsoft, Sybase, and Informix. The Practical SQL Handbook is the most complete reference available for day-to-day SQL implementations.
0-201-70309-2 • Paperback with CD-ROM • 512 pages • © 2001
Practical SQL The Sequel Judith S. Bowman
Written by a co-author of the best-selling Practical SQL Handbook, Practical SQL: The Sequel picks up where the first book leaves off. It goes beyond basic SQL query structure to explore the complexities of using SQL for everyday business needs. It will help you make the transition from classroom to reality, where you must design, fix, and maintain im- perfect SQL systems. For those who are working with SQL systems—or preparing to do so—this book offers information organized by use rather than by feature. Readers can turn to specific business problems and learn how to solve them with the appropriate SQL features. In particular, the sequel focuses on the real-world challenges of dealing with legacy sys- tems, inherited problematic code, dirty data, and query tuning for better performance.
0-201-61638-6 • Paperback with CD-ROM • 352 pages • © 2001
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From the Library of Stephen Benoit
- Contents
- Foreword
- Preface (Second Edition)
- Preface (First Edition)
- Introduction
- What’s New in the Second Edition
- Who Should Read This Book
- The Purpose of This Book
- How to Read This Book
- How This Book Is Organized
- Part I: Relational Database Design
- Part II: The Design Process
- Part III: Other Database-Design Issues
- Part IV: Appendixes
- A Word About the Examples and Techniques in This Book
- A New Approach to Learning
- PART I: RELATIONAL DATABASE DESIGN
- Chapter 1: The Relational Database
- Topics Covered in This Chapter
- Types of Databases
- Early Database Models
- The Relational Database Model
- Relational Database Management Systems
- Beyond the Relational Model
- What the Future Holds
- Summary
- Review Questions
- Chapter 2: Design Objectives
- Topics Covered in This Chapter
- Why Should You Be Concerned with Database Design?
- The Importance of Theory
- The Advantage of Learning a Good Design Methodology
- Objectives of Good Design
- Benefits of Good Design
- Database-Design Methods
- Summary
- Review Questions
- Chapter 3: Terminology
- Topics Covered in This Chapter
- Why This Terminology Is Important
- Value-Related Terms
- Structure-Related Terms
- Relationship-Related Terms
- Integrity-Related Terms
- Summary
- Review Questions
- PART II: THE DESIGN PROCESS
- Chapter 4: Conceptual Overview
- Topics Covered in This Chapter
- The Importance of Completing the Design Process
- Defining a Mission Statement and Mission Objectives
- Analyzing the Current Database
- Creating the Data Structures
- Determining and Establishing Table Relationships
- Determining and Defining Business Rules
- Determining and Defining Views
- Reviewing Data Integrity
- Summary
- Review Questions
- Chapter 5: Starting the Process
- Topics Covered in This Chapter
- Conducting Interviews
- The Case Study: Mike’s Bikes
- Defining the Mission Statement
- Defining the Mission Objectives
- Summary
- Review Questions
- Chapter 6: Analyzing the Current Database
- Topics Covered in This Chapter
- Getting to Know the Current Database
- Conducting the Analysis
- Looking at How Data Is Collected
- Looking at How Information Is Presented
- Conducting Interviews
- Interviewing Users
- Interviewing Management
- Compiling a Complete List of Fields
- Summary
- Review Questions
- Chapter 7: Establishing Table Structures
- Topics Covered in This Chapter
- Defining the Preliminary Table List
- Defining the Final Table List
- Associating Fields with Each Table
- Refining the Fields
- Refining the Table Structures
- Summary
- Review Questions
- Chapter 8: Keys
- Topics Covered in This Chapter
- Why Keys Are Important
- Establishing Keys for Each Table
- Table-Level Integrity
- Reviewing the Initial Table Structures
- Summary
- Review Questions
- Chapter 9: Field Specifications
- Topics Covered in This Chapter
- Why Field Specifications Are Important
- Field-Level Integrity
- Anatomy of a Field Specification
- Using Unique, Generic, and Replica Field Specifications
- Defining Field Specifications for Each Field in the Database
- Summary
- Review Questions
- Chapter 10: Table Relationships
- Topics Covered in This Chapter
- Why Relationships Are Important
- Types of Relationships
- Identifying Existing Relationships
- Establishing Each Relationship
- Refining All Foreign Keys
- Establishing Relationship Characteristics
- Relationship-Level Integrity
- Summary
- Review Questions
- Chapter 11: Business Rules
- Topics Covered in This Chapter
- What Are Business Rules?
- Categories of Business Rules
- Defining and Establishing Business Rules
- Validation Tables
- Reviewing the Business Rule Specifications Sheets
- Summary
- Review Questions
- Chapter 12: Views
- Topics Covered in This Chapter
- What Are Views?
- Anatomy of a View
- Determining and Defining Views
- Summary
- Review Questions
- Chapter 13: Reviewing Data Integrity
- Topics Covered in This Chapter
- Why You Should Review Data Integrity
- Reviewing and Refining Data Integrity
- Assembling the Database Documentation
- Done at Last!
- Summary
- PART III: OTHER DATABASE-DESIGN ISSUES
- Chapter 14: Bad Design—What Not to Do
- Topics Covered in This Chapter
- Flat-File Design
- Spreadsheet Design
- Database Design Based on the Database Software
- A Final Thought
- Summary
- Chapter 15: Bending or Breaking the Rules
- Topics Covered in This Chapter
- When May You Bend or Break the Rules?
- Documenting Your Actions
- Summary
- In Closing
- PART IV: APPENDIXES
- Appendix A: Answers to Review Questions
- Chapter 1
- Chapter 2
- Chapter 3
- Chapter 4
- Chapter 5
- Chapter 6
- Chapter 7
- Chapter 8
- Chapter 9
- Chapter 10
- Chapter 11
- Chapter 12
- Appendix B: Diagram of the Database-Design Process
- Appendix C: Design Guidelines
- Defining and Establishing Field Specific Business Rules
- Defining and Establishing Relationship Specific Business Rules
- Elements of a Candidate Key
- Elements of a Foreign Key
- Elements of a Primary Key
- Elements of the Ideal Field
- Elements of the Ideal Table
- Field-Level Integrity
- Guidelines for Composing a Field Description
- Guidelines for Composing a Table Description
- Guidelines for Creating Field Names
- Guidelines for Creating Table Names
- Identifying Relationships
- Identifying View Requirements
- Interview Guidelines
- Mission Statements
- Mission Objectives
- Relationship-Level Integrity
- Resolving a Multivalued Field
- Table-Level Integrity
- Appendix D: Documentation Forms
- Appendix E: Database-Design Diagram Symbols
- Appendix F: Sample Designs
- Appendix G: Recommended Reading
- Glossary
- A
- B
- C
- D
- E
- F
- H
- I
- K
- L
- M
- N
- O
- P
- Q
- R
- S
- T
- U
- V
- W
- Z
- References
- Index
- A
- B
- C
- D
- E
- F
- G
- H
- I
- J
- K
- L
- M
- N
- O
- P
- Q
- R
- S
- T
- U
- V
- W
- Z
