Simsion G.C., Witt G.C. Data Modeling Essentials

Elsevier – 2005, 560 pages
ISBN: 0126445516Data 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 perspec.Chapter I - What Is Data Modeling?
Introduction. A Data-Centered Perspective. A Simple Example. Design, Choice, and Creativity. Why Is the Data Model Important?. What Makes a Good Data Model?. Performance. Database Design Stages and Deliverables. Where Do Data Models Fit In?. Who Should Be Involved in Data Modeling?. Is Data Modeling Still Relevant?. Alternative Approaches to Data Modeling. Terminology. Where to from Here?—An Overview of Part. Summary.Chapter II - Basics of Sound Structure
Introduction . An Informal Example of Normalization . Relational Notation . A More Complex Example . Determining Columns . Repeating Groups and First Normal Form . Second and Third Normal Forms . Definitions and a Few Refinements . Choice, Creativity, and Normalization . Terminology . Summary.Chapter III - The Entity-Relationship Approach
Introduction . A Diagrammatic Representation . The Top-Down Approach: Entity-Relationship Modeling . Entity Classes . Relationships . Attributes . Myths and Folklore . Creativity and E-R Modeling . Summary.Chapter IV - Subtypes and Supertypes
Introduction . Different Levels of Generalization . Rules Versus Stability . Using Subtypes and Supertypes . Subtypes and Supertypes as Entity Classes . Diagramming Conventions . Definitions . Attributes of Supertypes and Subtypes . Non-Overlapping and Exhaustive . Overlapping Subtypes and Roles . Hierarchy of Subtypes . Benefits of Using Subtypes and Supertypes . When Do We Stop Supertyping and Subtyping? . Generalization of Relationships . Theoretical Background . Summary.Chapter V - Attributes and Columns
Introduction . Attribute Definition . Attribute Disaggregation: One Fact Per Attribute . Types of Attributes . Attribute Names . Attribute Generalization . Summary.Chapter VI - Primary Keys and Identity
Basic Requirements and Trade-Offs . Basic Technical Criteria . Surrogate Keys . Structured Keys . Multiple Candidate Keys . Guidelines for Choosing Keys . Partially-Null Keys . Summary.Chapter VII - Extensions & Alternatives
Introduction . Extensions to the Basic E-R Approach . The Chen E-R Approach . Using UML Object Class Diagrams . Summary.Chapter VIII - Organizing the Data Modeling Task
Data Modeling in the Real World . Key Issues in Project Organization . Roles and Responsibilities . Partitioning Large Projects . Maintaining the Model . Packaging It Up . Summary.Chapter IX - The Business Requirements
Purpose of the Requirements Phase . The Business Case . Interviews and Workshops . Riding the Trucks . Existing Systems and Reverse Engineering . Process Models . Object Class Hierarchies . Summary.Chapter X - Conceptual Data Modeling
Designing Real Models. Learning from Designers in Other Disciplines. Starting the Modeling. Patterns and Generic Models. Bottom-Up Modeling. Top-Down Modeling. When the Problem is Too Complex. Hierarchies, Networks, and Chains. One-to-One Relationships. Developing Entity Class Definitions. Handling Exceptions. The Right Attitude. Evaluating the Model. Direct Review of Data Model Diagrams. Comparison with the Process Model. Testing the Model with Sample Data. Prototypes. The Assertions Approach. Summary.Chapter XI - Logical Database Design
Introduction. Overview of the Transformations Required. Table Specification. Basic Column Definition. Primary Key Specification. Foreign Key Specification. Table and Column Names. Logical Data Model Notations. Summary.Chapter XII - Physical Database Design
Introduction. Inputs to Database Design. Options Available to the Database Designer. Design Decisions Which Do Not Affect Program Logic. Crafting Queries to Run Faster. Logical Schema Decisions. Views. Summary.Chapter XIII - Advanced Normalization
Introduction. Introduction to the Higher Normal Forms. Boyce-Codd Normal Form. Fourth Normal Form (NF) and Fifth Normal Form (NF). Beyond NF: Splitting Tables Based on Candidate Keys. Other Normalization Issues. Advanced Normalization in Perspective. Summary.Chapter XIV - Modeling Business Rules
Introduction. Types of Business Rules. Discovery and Verification of Business Rules. Documentation of Business Rules. Implementing Business Rules. Rules on Recursive Relationships. Summary.Chapter XV - Time-Dependent Data
The Problem. When Do We Add the Time Dimension?. Audit Trails and Snapshots. Sequences and Versions. Handling Deletions. Archiving. Modeling Time-Dependent Relationships. Date Tables. Temporal Business Rules. Changes to the Data Structure. Putting it into Practice. Summary.Chapter XVI - Modeling for Data Warehouses and Data Marts
Introduction. Characteristics of Data Warehouses and Data Marts. Quality Criteria for Warehouse and Mart Models. The Basic Design Principle. Modeling for the Data Warehouse. Modeling for the Data Mart. Summary.Chapter XVII - Enterprise Data Models and Data Management
Introduction. Data Management. Classification of Existing Data. A Target for Planning. A Context for Specifying New Databases. Guidance for Database Design. Input to Business Planning. Specification of an Enterprise Database. Characteristics of Enterprise Data Models. Developing an Enterprise Data Model. Choice, Creativity, and Enterprise Data Models. Summary.