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Data Modeling Essentials
- Auteur(s) : Graeme C. Simsion , Graham C. Witt
- Editeur : Elsevier
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Nombre de pages : 532 pages
- Date de parution : 15/12/2004 (3e édition)
Résumé
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 delve into advanced subjects, including business rules, data warehousing, and 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.
Features :
- 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 new 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
- Extensive online component including course notes and other teaching aids (www.mkp.com)
Sommaire
- Preface
- What Is Data Modeling?
- Basics of Sound Structure
- The Entity-Relationship Approach
- Subtypes and Supertypes
- Attributes and Columns
- Primary Keys and Identity
- Extensions & Alternatives
- Organizing the Data Modeling Task
- The Business Requirements
- Conceptual Data Modeling
- Logical Database Design
- Physical Database Design
- Advanced Normalization
- Modeling Business Rules
- Time-Dependent Data
- Modeling for Data Warehouses and Data Marts
- Enterprise Data Models and Data Management
- Further Reading
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