Data Modeling Essentials

ISBN-13: 9780126445510 / Angielski / Miękka / 2004 / 560 str.

Aust University of Melbourne Graeme Simsion (Senior Fellow; Australia) Sydney Graham Witt (Independent Consultant

Opis

Data Modeling Essentials, Third Edition, covers the basics of data modeling while focusing on developing a facility in techniques, rather than a simple familiarization with "the rules." In order to enable students to apply the basics of data modeling to real models, the book addresses the realities of developing systems in real-world situations by assessing the merits of a variety of possible solutions as well as using language and diagramming methods that represent industry practice. This revised edition has been given significantly expanded coverage and reorganized for greater reader comprehension even as it retains its distinctive hallmarks of readability and usefulness. Beginning with the basics, the 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. It includes an entirely new section discussing the development of logical and physical modeling, along with new material describing a powerful technique for model verification. It also provides an excellent resource for additional lectures and exercises. This text is the ideal reference for data modelers, data architects, database designers, DBAs, and systems analysts, as well as undergraduate and graduate-level students looking for a real-world perspective.

• Thorough coverage of the fundamentals and relevant theory.
• Recognition and support for the creative side of the process.
• Expanded coverage of applied data modeling includes new chapters on logical and physical database design.
• New material describing a powerful technique for model verification.
• Unique coverage of the practical and human aspects of modeling, such as working with business specialists, managing change, and resolving conflict.

Recenzje

"The perfect balance of theory and practice, giving the reader both the foundation and the tools to deliver high-quality data models." --Karen Lopez, Principal, InfoAdvisors, Inc.

"The complete guide to data modeling for the reflective practitioner. Students like this book and so do I -- it is clear and accessible without sacrificing rigor." --Professor Graeme Shanks, School of Business Systems, Monash University, Australia

"A unique, practical and comprehensive guide, providing an invaluable resource to anyone involved in data modeling from the novice to the expert data modeler." --Len Silverston, author of The Data Model Resource Book, Volumes 1 and 2.

"Includes an extraordinary amount of good, useful, and well articulated information about the field." --David Hay, President, Essential Strategies, Inc. and author of Data Model Patterns

"Data Modeling Essentials is a fresh look at an old topic...much more accesible and refreshing in its tone and attitude. Simsion's explanations are very clear and his examples easy to follow...This book is useful for both beginners and experienced data modelers who want a new innovative approach to the important task of documenting data requirements." - The Bridge --Barbara A. Carkenord

"The book is extremely well-written. It is humorous at times, full of useful anecdotes, and follows a very logical sequence...In summary, I found Data Modeling Essentials, Third Edition, very useful for data modelers at any level of experience." --DM Review

Spis treści

Part I: Basics 1. What is Data Modeling? 2. Basics of Good Structure 3. The Entity-Relationship Approach 4. Subtypes and Supertypes 5. Attributes and Columns 6. Primary Keys and Identity 7. Extensions and Alternatives

Part II: Putting it Together 8. Organizing the Data Modeling Task 9. Understanding the Business Requirements 10. Conceptual Modeling 11. Logical Database Design 12. Physical Database Design

Part III: Advanced Topics 13. Advanced Normalization 14. Modeling Business Rules 15. Time-Dependent Data 16. Modeling for Data Warehouses and Data Marts 17. Enterprise Data Models and Data Management