Bookpool: Database Modeling and Design, 4th Edition

Database systems and database design technology have undergone significant evolution in recent years. The relational data model and relational database systems dominate business applications; in turn, they are extended by other technologies like data warehousing, OLAP, and data mining. How do you model and design your database application in consideration of new technology or new business needs?

In the extensively revised fourth edition, you'll get clear explanations, lots of terrific examples and an illustrative case, and the really practical advice you have come to count on--with design rules that are applicable to any SQL-based system. But you'll also get plenty to help you grow from a new database designer to an experienced designer developing industrial-sized systems.

Chapter 1 Introduction
1.1 Data and Database Management
1.2 The Database Life Cycle
1.2 Conceptual Data Modeling
1.4 Summary
Literature Summary

Chapter 2 The Entity-Relationship Model
2.1 Fundamental ER Constructs
2.1.1 Basic Objects: Entities, Relationships, Attributes
2.1.2 Degree of a Relationship
2.1.3 Connectivity of a Relationship
2.1.4 Attributes of a Relationship
2.1.5 Existence of an Entity in a Relationship
2.1.6 Alternative Conceptual Data Modeling Notations
2.2 Advanced ER Constructs
2.2.1 Generalization: Supertypes and Subtypes
2.2.2 Aggregation
2.2.3 Ternary Relationships
2.2.4 General n-ary Relationships
2.2.5 Exclusion constraint
2.2.6 Referential Integrity
2.3 Summary
Literature Summary

Chapter 3 Unified Modeling Language
3.1 Class Diagrams
3.1.1 Class Diagram Notation Description
3.1.2 Class Diagrams for Software Design
3.1.3 Class Diagrams for Database Design
3.2 Activity Diagrams
3.2.1 Activity Diagram Notation Description
3.2.2 Activity Diagrams for Software Design
3.2.3 Activity Diagrams for Workflow
3.3 Rules of Thumb for UML Usage
3.4 Summary
Literature Summary

Chapter 4 Requirements Analysis and Conceptual Data Modeling
4.1 Introduction
4.2 Requirements Analysis
4.3 Conceptual Data Modeling
4.3.1 Classify Entities and Attributes
4.3.2 Identify the Generalization Hierarchies
4.3.3 Define Relationships
4.3.4 Example of Data Modeling: Company Project Database
4.4 View Integration
4.4.1 Pre-integration Analysis
4.4.2 Comparison of Schemas
4.4.3 Conformation of Schemas
4.4.4 Merging and Restructuring of Schemas
4.4.5 Example of View Integration
4.5 Entity Clustering for ER Models
4.5.1 Clustering Concepts
4.5.2 Grouping Operations
4.5.3 Clustering Technique
4.6 Summary
Literature Summary

Chapter 5 Transforming the Conceptual Data Model to SQL
5.1 Transformation Rules and SQL Constructs
5.1.1 Binary Relationships
5.1.2 Binary Recursive Relationships
5.1.3 Ternary and n-ary Relationships
5.1.4 Generalization and Aggregation
5.1.5 Multiple Relationships
5.1.6 Weak Entities
5.2 Transformation Steps
5.2.1 Entity Transformation
5.2.2 Many-to-Many Binary Relationship Transformation
5.2.3 Ternary Relationship Transformation
5.2.4 Example of ER-to-SQL Transformation
5.3 Summary
Literature Summary

Chapter 6 Normalization
6.1 Fundamentals of Normalization
6.1.1 First Normal Form
6.1.2 Superkeys, Candidate Keys, and Primary Keys
6.1.3 Second Normal Form
6.1.4 Third Normal Form
6.1.5 Boyce-Codd Normal Form
6.2 The Design of Normalized Tables: Simple Example
6.3 Normalization of Candidate Tables Derived from ER Diagrams
6.4 Determining the Minimum Set of 3NF Tables
6.4.1 Elimination of Extraneous Attributes
6.4.2 Search for a Nonredundant Cover
6.4.3 Partitioning of the Nonredundant Cover
6.4.4 Merge of Equivalent Keys
6.4.5 Definition of Tables
6.5 Fourth and Fifth Normal Forms
6.5.1 Multivalued Dependencies
6.5.2 Fourth Normal Form
6.5.3 Decomposing Tables to 4NF
6.5.4 Fifth Normal Form
6.6 Summary
Literature Summary

Chapter 7 An Example of Logical Database Design
7.1 Requirements Specification
7.2 Logical Design
7.3 Summary

Chapter 8 Business Intelligence
8.1 Data Warehousing
8.1.1 Overview of Data Warehousing
8.1.2 Logical Design
8.2 On-Line Analytical Processing (OLAP)
8.2.1 The Exponential Explosion of Views
8.2.2 Overview of OLAP
8.2.3 View Size Estimation
8.2.4 Selection of Material Views
8.2.5 View Maintenance
8.2.6 Query Optimization
8.3 Data Mining
8.3.1 Forecasting
8.3.2 Text Mining
8.4 Summary
Literature Summary

Chapter 9 CASE Tools for Logical Database Design
9.1 Introduction to Software Tools
9.2 The Key Capabilities to Watch For
9.3 The Basics
9.4 Generating a Database From a Design
9.5 Database Support
9.6 Collaborative Support
9.7 Distributed Development
9.8 Application Lifecycle Tooling Integration
9.9 Design Compliance Checking
9.10 Reporting
9.11 Semi-Structured Data, XML
9.12 Summary
Literature Summary

Appendix The Basics of SQL
A.1 SQL Names and Operators
A.2 Data Definition Language (DDL)
A.3 Data Manipulation Language (DML)
A.3.1 SQL Select Command
A.3.2 SQL Update Commands
A.3.3 Referential Integrity
A.3.4 SQL Views
References

Exercises for Logical Design
Solutions to Selected Exercises
Glossary

About the Authors

Toby J. Teorey is a professor in the Electrical Engineering and Computer Science Department at the University of Michigan, Ann Arbor. He received his B.S. and M.S. degrees in electrical engineering from the University of Arizona, Tucson, and a Ph.D. in computer sciences from the University of Wisconsin, Madison. He was general chair of the 1981 ACM SIGMOD Conference and program chair for the 1991 Entity-Relationship Conference. Professor Teorey’s current research focuses on database design and data warehousing, OLAP, advanced database systems, and performance of computer networks. He is a member of the ACM and the IEEE Computer Society.

Sam Lightstone is a Senior Technical Staff Member and Development Manager with IBM's DB2 Universal Database development team. He is the cofounder and leader of DB2's autonomic computing R&D effort. He is also a member of IBM's Autonomic Computing Architecture Board, and in 2003 he was elected to the Canadian Technical Excellence Council, the Canadian affiliate of the IBM Academy of Technology. His current research includes numerous topics in autonomic computing and relational DBMSs including: automatic physical database design, adaptive self tuning resources, automatic administration, benchmarking methodologies, and system control. Mr. Lightstone is an IBM Master Inventor with over 25 patents and patents pending, and he has published widely on Autonomic Computing for relational database systems. He has been with IBM since 1991.Author of: Database Modeling and Design

Tom Nadeau is the founder of Aladdin Software (aladdinsoftware.com) and works in the area of data and text mining. He received his B.S. degree in computer science and M.S. and Ph.D. degrees in electrical engineering and computer science from the University of Michigan, Ann Arbor. His technical interests include data warehousing, OLAP, data mining and machine learning. He won the best paper award at the 2001 IBM CASCON Conference.

Nov 4, 2005 Sue R. Montgomery from Canada
Really great book. Excellent depth on the topics.
This book is really great, both as an introduction and as a reference for experienced database designers. I was impressed by the way the book covered the full scope of logical design, entity relationship modeling , transformations to SQL, and tooling. What impressed me most is the book's ability to cover the material from both a practical "gimme the issues" point of view and also as an academic well researched and referenced text. Great book. I highly recommend it.

Table of Contents

About the Authors