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 To order this title, and for more information, click here
Third Edition
By
Graeme Simsion, Senior Fellow, University of Melbourne, Australia
Graham Witt, Independent Consultant, Sydney, Australia
Description
Data Modeling Essentials, Third Edition provides expert tutelage for data modelers, business analysts and systems designers at
all levels. Beginning with the basics, this book provides a thorough grounding in theory before guiding the reader through the various
stages of applied data modeling and database design. Later chapters address advanced subjects, including business rules, data warehousing,
enterprise-wide modeling and data management.
The third edition of this popular book retains its distinctive hallmarks of readability
and usefulness, but has been given significantly expanded coverage and reorganized for greater reader comprehension. Authored by two
leaders in the field, Data Modeling Essentials, Third Edition is the ideal reference for professionals and students looking for
a real-world perspective.
Audience
data modelers, data architects, database designers, DBAs, systems analysts; undergraduate and graduate-level students
Contents
Contents
Preface
Chapter 1 - What Is Data Modeling?
1.1 Introduction
1.2 A Data-Centered Perspective
1.3 A Simple
Example
1.4 Design, Choice, and Creativity
1.5 Why Is the Data Model Important?
1.6 What Makes a Good Data Model?
1.7 Performance
1.8
Database Design Stages and Deliverables
1.9 Where Do Data Models Fit In?
1.10 Who Should Be Involved in Data Modeling?
1.11 Is Data Modeling
Still Relevant?
1.12 Alternative Approaches to Data Modeling
1.13 Terminology
1.14 Where to from Here??An Overview of Part 1
1.15 Summary
Chapter 2 - Basics of Sound Structure
2.1 Introduction
2.2 An Informal Example of Normalization
2.3 Relational Notation
2.4 A
More Complex Example
2.5 Determining Columns
2.6 Repeating Groups and First Normal Form
2.7 Second and Third Normal Forms
2.8 Definitions
and a Few Refinements
2.9 Choice, Creativity, and Normalization
2.10 Terminology 60
2.11 Summary 61
Chapter 3 - The Entity-Relationship
Approach
3.1 Introduction
3.2 A Diagrammatic Representation
3.3 The Top-Down Approach: Entity-Relationship Modeling
3.4 Entity Classes
3.5 Relationships
3.6 Attributes
3.7 Myths and Folklore
3.8 Creativity and E-R Modeling
3.9 Summary
Chapter 4 - Subtypes and Supertypes
4.1 Introduction
4.2 Different Levels of Generalization
4.3 Rules Versus Stability
4.4 Using Subtypes and Supertypes
4.5 Subtypes and
Supertypes as Entity Classes
4.6 Diagramming Conventions
4.7 Definitions
4.8 Attributes of Supertypes and Subtypes
4.9 Non-Overlapping
and Exhaustive
4.10 Overlapping Subtypes and Roles
4.11 Hierarchy of Subtypes
4.12 Benefits of Using Subtypes and Supertypes
4.13 When
Do We Stop Supertyping and Subtyping?
4.14 Generalization of Relationships
4.15 Theoretical Background
4.16 Summary
Chapter 5 - Attributes
and Columns
5.1 Introduction
5.2 Attribute Definition
5.3 Attribute Disaggregation: One Fact Per Attribute
5.4 Types of Attributes
5.5 Attribute Names
5.6 Attribute Generalization
5.7 Summary
Chapter 6 - Primary Keys and Identity
6.1 Basic Requirements and
Trade-Offs
6.2 Basic Technical Criteria
6.3 Surrogate Keys
6.4 Structured Keys
6.5 Multiple Candidate Keys
6.6 Guidelines for Choosing
Keys
6.7 Partially-Null Keys
6.8 Summary
Chapter 7 - Extensions & Alternatives
7.1 Introduction
7.2 Extensions to the Basic E-R
Approach
7.3 The Chen E-R Approach
7.4 Using UML Object Class Diagrams
7.5 Summary
Chapter 8 - Organizing the Data Modeling Task
8.1 Data Modeling in the Real World
8.2 Key Issues in Project Organization
8.3 Roles and Responsibilities
8.4 Partitioning Large Projects
8.5 Maintaining the Model
8.6 Packaging It Up
8.7 Summary
Chapter 9 - The Business Requirements
9.1 Purpose of the Requirements
Phase
9.2 The Business Case
9.3 Interviews and Workshops
9.4 Riding the Trucks
9.5 Existing Systems and Reverse Engineering
9.6 Process
Models
9.7 Object Class Hierarchies
9.8 Summary
Chapter 10 - Conceptual Data Modeling
10.1 Designing Real Models
10.2 Learning
from Designers in Other Disciplines
10.3 Starting the Modeling
10.4 Patterns and Generic Models
10.5 Bottom-Up Modeling
10.6 Top-Down
Modeling
10.7 When the Problem is Too Complex
10.8 Hierarchies, Networks, and Chains
10.9 One-to-One Relationships
10.10 Developing Entity
Class Definitions
10.11 Handling Exceptions
10.12 The Right Attitude
10.13 Evaluating the Model
10.14 Direct Review of Data Model Diagrams
10.15 Comparison with the Process Model
10.16 Testing the Model with Sample Data
10.17 Prototypes
10.18 The Assertions Approach
10.19
Summary
Chapter 11 - Logical Database Design
11.1 Introduction
11.2 Overview of the Transformations Required
11.3 Table Specification
11.4 Basic Column Definition
11.5 Primary Key Specification
11.6 Foreign Key Specification
11.7 Table and Column Names
11.8 Logical Data
Model Notations
11.9 Summary
Chapter 12 - Physical Database Design
12.1 Introduction
12.2 Inputs to Database Design
12.3 Options
Available to the Database Designer
12.4 Design Decisions Which Do Not Affect Program Logic
12.5 Crafting Queries to Run Faster
12.6 Logical
Schema Decisions
12.7 Views
12.8 Summary
Chapter 13 - Advanced Normalization
13.1 Introduction
13.2 Introduction to the Higher
Normal Forms
13.3 Boyce-Codd Normal Form
13.4 Fourth Normal Form (4NF) and Fifth Normal Form (5NF)
13.5 Beyond 5NF: Splitting Tables
Based on Candidate Keys
13.6 Other Normalization Issues
13.7 Advanced Normalization in Perspective
13.8 Summary
Chapter 14 - Modeling
Business Rules
14.1 Introduction
14.2 Types of Business Rules
14.3 Discovery and Verification of Business Rules
14.4 Documentation
of Business Rules
14.5 Implementing Business Rules
14.6 Rules on Recursive Relationships
14.7 Summary
Chapter 15 - Time-Dependent
Data
15.1 The Problem
15.2 When Do We Add the Time Dimension?
15.3 Audit Trails and Snapshots
15.4 Sequences and Versions
15.5 Handling
Deletions
15.6 Archiving
15.7 Modeling Time-Dependent Relationships
15.8 Date Tables
15.9 Temporal Business Rules
15.10 Changes to the
Data Structure
15.11 Putting it into Practice
15.12 Summary
Chapter 16 - Modeling for Data Warehouses and Data Marts
16.1 Introduction
16.2 Characteristics of Data Warehouses and Data Marts
16.3 Quality Criteria for Warehouse and Mart Models
16.4 The Basic Design Principle
16.5 Modeling for the Data Warehouse
16.6 Modeling for the Data Mart
16.7 Summary
Chapter 17 - Enterprise Data Models and Data Management
17.1 Introduction
17.2 Data Management
17.3 Classification of Existing Data
17.4 A Target for Planning
17.5 A Context for Specifying
New Databases
17.6 Guidance for Database Design
17.7 Input to Business Planning
17.8 Specification of an Enterprise Database
17.9 Characteristics
of Enterprise Data Models
17.10 Developing an Enterprise Data Model
17.11 Choice, Creativity, and Enterprise Data Models
17.12 Summary
Further Reading
Bibliographic & ordering Information
Paperback, 560 pages, publication date: NOV-2004
ISBN-13: 978-0-12-644551-0
ISBN-10: 0-12-644551-6
Imprint: MORGAN KAUFFMAN
Price: Order form
GBP 39.99
USD 70.95
EUR 57.95
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Last update: 12 Aug 2008
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