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Chapter7LogicalDatabaseDesign.ppt
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Chapter 7
Logical Database Design

BLCN-534: Fundamentals of Database Systems

Chapter Objectives

  • Describe the concept of logical database design.
  • Design relational databases by converting entity-relationship diagrams into relational tables.
  • Describe the data normalization process.
  • Perform the data normalization process.
  • Test tables for irregularities using the data normalization process.

Logical Database Design

  • The process of deciding how to arrange the attributes of the entities in the business environment into database structures, such as the tables of a relational database.
  • The goal is to create well structured tables that properly reflect the company’s business environment.

Logical Design of Relational Database Systems

  • (1) The conversion of E-R diagrams into relational tables.
  • (2) The data normalization technique.
  • (3) The use of the data normalization technique to test the tables resulting from the E-R diagram conversions.

Converting E-R Diagrams into Relational Tables

  • Each entity will convert to a table.
  • Each many-to-many relationship or associative entity will convert to a table.
  • During the conversion, certain rules must be followed to ensure that foreign keys appear in their proper places in the tables.

Converting a Simple Entity

  • The table simply contains the attributes that were specified in the entity box.
  • Salesperson Number is underlined to indicate that it is the unique identifier of the entity and the primary key of the table.

Converting Entities in Binary Relationships: One-to-One

  • There are three options for designing tables to represent this data.

One-to-One: Option #1

  • The two entities are combined into one relational table.

One-to-One: Option #2

Separate tables for the SALESPERSON and OFFICE entities, with Office Number as a foreign key in the SALESPERSON table.

One-to-One: Option #3

  • Separate tables for the SALESPERSON and OFFICE entities, with Salesperson Number as a foreign key in the OFFICE table.

Converting Entities in Binary Relationships: One-to-Many

  • The unique identifier of the entity on the “one side” of the one-to-many relationship is placed as a foreign key in the table representing the entity on the “many side.”
  • So, the Salesperson Number attribute is placed in the CUSTOMER table as a foreign key.

Converting Entities in Binary Relationships: One-to-Many

Converting Entities in Binary Relationships: Many-to-Many

  • E-R diagram with the many-to-many binary relationship and the equivalent diagram using an associative entity.

Converting Entities in Binary Relationships: Many-to-Many

  • An E-R diagram with two entities in a many-to-many relationship converts to three relational tables.
  • Each of the two entities converts to a table with its own attributes but with no foreign keys (regarding this relationship).
  • In addition, there must be a third “many-to-many” table for the many-to-many relationship.

Converting Entities in Binary Relationships: Many-to-Many

  • The primary key of SALE is the combination of the unique identifiers of the two entities in the many-to-many relationship. Additional attributes are the intersection data.

Converting Entities in Unary Relationships: One-to-One

  • With only one entity type involved and with a one-to-one relationship, the conversion requires only one table.

Converting Entities in Unary Relationships: One-to-Many

Very similar to the one-to-one unary case.

Converting Entities in Unary Relationships: Many-to-Many

  • This relationship requires two tables in the conversion.
  • The PRODUCT table has no foreign keys.

Converting Entities in Unary Relationships: Many-to-Many

  • A second table is created since in the conversion of a many-to-many relationship of any degree — unary, binary, or ternary — the number of tables will be equal to the number of entity types (one, two, or three, respectively) plus one more table for the many-to-many relationship.

Converting Entities in Ternary Relationships

  • The primary key of the SALE table is the combination of the unique identifiers of the three entities involved, plus the Date attribute.

The Data Normalization Process

  • A methodology for organizing attributes into tables so that redundancy among the nonkey attributes is eliminated.
  • The output of the data normalization process is a properly structured relational database.

The Data Normalization Technique

  • Input:
  • all the attributes that must be incorporated into the database
  • a list of all the defining associations between the attributes (i.e., the functional dependencies).
  • a means of expressing that the value of one particular attribute is associated with a single, specific value of another attribute.
  • If we know that one of these attributes has a particular value, then the other attribute must have some other value.

General Hardware Environment: SALESPERSON and PRODUCT

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Functional Dependence

  • Salesperson Number is the determinant.
  • The value of Salesperson Number determines the value of Salesperson Name.
  • Salesperson Name is functionally dependent on Salesperson Number.

Salesperson Name

Salesperson Number

Steps in the Data Normalization Process

First Normal Form

Second Normal Form

Third Normal Form

The Data Normalization Process

  • Once the attributes are arranged in third normal form, the group of tables that they comprise is a well-structured relational database with no data redundancy.
  • A group of tables is said to be in a particular normal form if every table in the group is in that normal form.
  • The data normalization process is progressive.
  • For example, if a group of tables is in second normal form, it is also in first normal form.

General Hardware Company: First Normal Form

  • The attributes under consideration have been listed in one table, and a primary key has been established.
  • The number of records has been increased so that every attribute of every record has just one value.
  • The multivalued attributes have been eliminated.

General Hardware Company: First Normal Form

  • First normal form is merely a starting point in the normalization process.
  • First normal form contains a great deal of data redundancy.
  • Three records involve salesperson 137, so there are three places in which his name is listed as Baker, his commission percentage is listed as 10, and so on.
  • Two records involve product 19440 and this product’s name is listed twice as Hammer and its unit price is listed twice as 17.50.

General Hardware Company: Second Normal Form

  • No Partial Functional Dependencies
  • Every nonkey attribute must be fully functionally dependent on the entire key of that table.
  • A nonkey attribute cannot depend on only part of the key.

General Hardware Company: Second Normal Form

  • In SALESPERSON, Salesperson Number is the sole primary key attribute. Every nonkey attribute of the table is fully defined just by Salesperson Number.
  • Similar logic for PRODUCT and QUANTITY tables.

General Hardware Company: Third Normal Form

  • Does not allow transitive dependencies in which one nonkey attribute is functionally dependent on another.
  • Nonkey attributes are not allowed to define other nonkey attributes.

General Hardware Company: Third Normal Form

  • Important points about the third normal form structure are:
  • It is completely free of data redundancy.
  • All foreign keys appear where needed to logically tie together related tables.
  • It is the same structure that would have been derived from a properly drawn entity-relationship diagram of the same business environment.

Candidate Keys as Determinants

  • There is one exception to the rule that in third normal form, nonkey attributes are not allowed to define other nonkey attributes.
  • The rule does not hold if the defining nonkey attribute is a candidate key of the table.
  • Candidate keys in a relation may define other nonkey attributes without violating third normal form.

Data Normalization Check

  • The basic idea in checking the structural worthiness of relational tables, created through E-R diagram conversion, with the data normalization rules is to:
  • Check to see if there are any partial functional dependencies.
  • Check to see if there are any transitive dependencies.

CREATE TABLE SALESPERSON

(SPNUM CHAR(3) PRIMARY KEY,

SPNAME CHAR(12)

COMMPERCT DECIMAL(3,0)

YEARHIRE CHAR(4)

OFFNUM CHAR(3) );

Dropping a Table with SQL

Creating a Table with SQL

DROP TABLE SALESPERSON;

CREATE VIEW EMPLOYEE AS

SELECT SPNUM, SPNAME, YEARHIRE

FROM SLAESPERSON;

Dropping a View with SQL

Creating a View with SQL

DROP VIEW EMPLOYEE ;

UPDATE SALESPERSON

SET COMMPERCT = 12

WHERE SPNUM = ‘204’;

The SQL Update, Insert, and Delete Commands

INSERT INTO SALESPERSON

VALUES

(‘489’, ‘Quinlan’, 15, ‘2011’, ‘59’);

DELETE FROM SALESPERSON

WHERE SPNUM = ‘186’;

Use Cases and Examples

Designing the General Hardware Company Database

Designing the Good Reading Bookstores Database

Designing the World Music Association Database

Designing the Lucky Rent-A-Car Database

General Hardware Company: Unnormalized Data

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General Hardware Company: First Normal Form

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General Hardware Company: Second Normal Form

General Hardware Company: Functional Dependencies

General Hardware Company: First Normal Form

Good Reading Bookstores: Functional Dependencies

World Music Association: Functional Dependencies

Lucky Rent-A-Car:
Functional Dependencies

General Hardware Company: Third Normal Form

General Hardware Company: Third Normal Form