The Data Modeling Handbook
A Best-Practice Approach to Building Quality Data Models
Michael Reingruber, William W. Gregory
362 pages, parution le 20/06/1995
Résumé
Here's a straight ahead, no-nonsense guide to building the
most accurate, complete and useful data models possible.
Have you ever wondered if your data model is
accurate? Or, if a model is really complete? Or, if it's possible for a model to be both technically perfect and of no use to your organization, and what to do about it?
If so, this book provides the answers to these and other crucial data modeling questions. While there are plenty of books that describe the characteristics of finished
data models, only The Data Modeling Handbook actually gets down to the details of building one. Packed with real-world examples, annotated diagrams, and a
wealth of rules and best practices, this field-tested guide provides hands-on guidance to building data models.
accurate? Or, if a model is really complete? Or, if it's possible for a model to be both technically perfect and of no use to your organization, and what to do about it?
If so, this book provides the answers to these and other crucial data modeling questions. While there are plenty of books that describe the characteristics of finished
data models, only The Data Modeling Handbook actually gets down to the details of building one. Packed with real-world examples, annotated diagrams, and a
wealth of rules and best practices, this field-tested guide provides hands-on guidance to building data models.
It delivers
- Clear, straightforward rules and guidelines
for judging model accuracy and completeness. - All rules in several notations, including IEDF1X, Martin, Chen, and Finkelstein.
- Detailed analysis of the most
popular modeling styles and demonstrations of how you can build great models using any type of notation. - Explanations of how to use your organization's
plans,
policies, objectives, and strategies to build accurate, complete and useful models. - Detailed guidance on establishing a continuous quality
evaluation program that's
easy to implement and follow. - Dozens of real-world examples and annotated diagrams illustrating each point covered.
- Descriptions of how to use CASE tools
most effectively to build high quality data models.
Table of contents
Data Modeling and Quality
Data Model Quality Assurance Programs
DATA MODELING RULES
Entity Rules
Attribute Rules
Relationship Rules
Generalization Hierarchy Rules
Data Model View Rules
Normalization Rules
Best Practices
Appendices
Index.
Caractéristiques techniques
| PAPIER | |
| Éditeur(s) | Wiley |
| Auteur(s) | Michael Reingruber, William W. Gregory |
| Parution | 20/06/1995 |
| Nb. de pages | 362 |
| EAN13 | 9780471052906 |
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