MIS480 1
Chapter -1 The Database Environment and Development Process
• The Database Environment and Development Process
• Chapter 1 (pp36-80)
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It is essential you to read the text book. These slides represent a summary of what was presented in the class and summary of what is
covered in the book. Relying purely on the slides will not guarantee you will pass this course.
The Database Environment and Development Process
• Modern Database Management
• 13th Edition
• Jeffrey A. Hoffer, V. Ramesh,
• Heikki Topi
© 2013 Pearson Education, Inc. Publishing as Prentice Hall 3
Course book:
Lesson Content
Introduction to the Course & Tutor
What is: Data? Information Database? DBMs? Data model? Metadata? Enterprise Data Model? Entity? Relational Database? ERP? Data Warehouse? SDLC? Logical and Physical schema?
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Get to know your tutor
• Dr. Syed Faizan Zaidi Joined AUM in August 2019.
Assistant Professor
Ph.D. Information Systems in 2017 from London Metropolitan University, London, UK
• What is a Database? • The storage of data for the purpose of processing.
Databases can be: • Non-electronic: Hospital Filing Cabinet, University Student record
files, Bank Sales Receipt files..etc
• Electronic: MS Access: Hospital Patient Records, Oracle: Students Records, Cobol: Bank Sales Records…
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Definitions p.36
• Metadata: data that describes the properties and context of user data.
• It is information about that data we are looking at.
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Definitions p.41
Traditional File Processing
• Traditional File system: also called a file processing system, stores and manages data in one or more separate files. • Used Excel, notepad, or similar applications to store data.
• File processing design approach was well suited to mainframe hardware and batch input.
• File processing design is less common today.
• File processing can be more efficient and cost less than a DBMS in certain situations but it is less effective and prone to errors.
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Traditional File Processing
• How are they different to Databases: • Database system: Organizing the data into tables, that form an
overall data structure.
• Compared to file processing, a database environment offers greater flexibility and efficiency.
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Disadvantages of File Processing
• Program-Data Dependence • All programs maintain metadata for each file they
use
• Duplication of Data • Different systems/programs have separate copies
of the same data
• Limited Data Sharing • No centralized control of data
• Lengthy Development Times • Programmers must design their own file formats
• Excessive Program Maintenance • 80% of information systems budget
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Elements of the Database Approach
• Data models • Enterprise Data Model–high-level entities and
relationships for the organization • Project Data Model –more detailed view, matching
data structure in database or data warehouse
• Entities • Noun form describing a person, place, object, event,
or concept. • Represent something we want to store in our
system. • Composed of attributes
• Relationships • Between entities • Usually one-to-many (1:M) or many-to-many (M:N)
• Relational Databases • Database method involving tables (relations)
representing entities and primary/foreign keys representing relationships.
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Figure 1-5 Components of the Database Environment
Components of the Database Environment
• Database–storehouse of the data
• Repository–centralized storehouse of metadata
• Database Management System (DBMS) –software for managing the database
• Application Programs–software using the data
• System Developers–personnel (people) responsible for designing databases and software
• Data/Database Administrators–personnel (people) responsible for maintaining the database
• CASE Tools–computer-aided software engineering
• User Interface–text and graphical displays to users
• End Users–people who use the applications and databases
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Two Approaches to Database and IS Development
• SDLC • System Development Life Cycle
• Detailed, well-planned development process
• Time-consuming, but comprehensive
• Long development cycle
• Prototyping • Rapid application development (RAD)
• Cursory attempt at conceptual data modeling
• Define database during development of initial prototype
• Repeat implementation and maintenance activities with new prototype versions
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Systems Development Life Cycle (see also Figure 1-7)
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Planning
Analysis
Physical Design
Implementation
Maintenance
Logical Design
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Prototyping Database Methodology (Figure 1-8)
Database Schema
External Schema User Views
Subsets of Conceptual Schema
Can be determined from business-function/data entity matrices
DBA determines schema for different users
Conceptual Schema E-R models–covered in Chapters 2 and 3
Internal Schema Logical structures–covered in Chapter 4
Physical structures–covered in Chapter 5
Different people
have different
views of the
database…these
are the external
schema
The internal
schema is the
underlying
design and
implementation
Figure 1-9 Three-schema architecture
Evolution of Database Systems
• Driven by four main objectives:
• Need for program-data independence reduced maintenance
• Desire to manage more complex data types and structures
• Ease of data access for less technical personnel
• Need for more powerful decision support platforms
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Evolution of Database Systems
The Range of Database Applications
• Personal databases
• Two-tier and N-tier Client/Server databases
• Enterprise applications • Enterprise resource planning (ERP) systems
• Data warehousing implementations
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Keywords:
Data, Information, Database, DBMs, Data model, Metadata, Enterprise Data Model, Entity, Relational Database, ERP, Data Warehouse, SDLC, Prototyping, Logical and Physical schema, Repository, Database Management System (DBMS), Application Programs, System Developers, Data/Database Administrators, CASE Tools, User Interface–text, End Users, Database Schema, External Schema, Conceptual Schema, and Internal Schema, Evaluation of Database, Hierarchical Database model, Network Database Model, Relational database model, Object-oriented database model, Personal database, Two-tier database, and N- tier database
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