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A Straightforward, No-Nonsense Guide to Building the Most Accurate, Complete, and Useful Data Models Possible. How do I know if my data model is accurate? When is a model really complete? Is it possible for a model to be both technically perfect and of no use to an organization, and what can I do to avoid that problem? This book provides answers to these and other crucial data modeling questions. While there are plenty of books that describe the characteristics of finished high-quality data models, only The Data Modeling Handbook gets down to the nitty-gritty of actually building one. Packed with real-world examples, annotated diagrams, and a wealth of rules and best practices, this field-tested guide provides experienced data modelers, architects, and engineers with hands-on guidance from two noted data management experts.
* The only book offering clear, straightforward rules and guidelines for judging model accuracy and completeness
* Presents all rules in several notations, including IDEF1X, Martin, Chen, and Finkelstein
* Compares and contrasts the most popular modeling styles and demonstrates how great models can be built using any type of notation
* Explains how to use an organization's plans, policies, objectives, and strategies to build accurate, complete, and useful models
* Offers detailed guidance to establishing a continuous quality evaluation program that's easy to implement and follow
* Packed with real-world examples and annotated diagrams illustrating each point covered
* Describes how to use Case tools most effectively to build high-quality models
- Sales Rank: #151611 in Books
- Published on: 1994-12-17
- Original language: English
- Number of items: 1
- Dimensions: 9.54" h x 1.00" w x 6.18" l, 1.53 pounds
- Binding: Hardcover
- 384 pages
From the Publisher
A straightforward explanation of how to combine good technique with business context in a self-regulating modeling process that results in the creation of useable models. Contains a series of rules and best practices in an organized reference format. Addresses transition to systems development and model management, presenting each rule in several notations. Includes numerous examples drawn from practical experience.
From the Back Cover
A Straightforward, No-Nonsense Guide to Building the Most Accurate, Complete, and Useful Data Models Possible. How do I know if my data model is accurate? When is a model really complete? Is it possible for a model to be both technically perfect and of no use to an organization, and what can I do to avoid that problem? This book provides answers to these and other crucial data modeling questions. While there are plenty of books that describe the characteristics of finished high-quality data models, only The Data Modeling Handbook gets down to the nitty-gritty of actually building one. Packed with real-world examples, annotated diagrams, and a wealth of rules and best practices, this field-tested guide provides experienced data modelers, architects, and engineers with hands-on guidance from two noted data management experts.
- The only book offering clear, straightforward rules and guidelines for judging model accuracy and completeness
- Presents all rules in several notations, including IDEF1X, Martin, Chen, and Finkelstein
- Compares and contrasts the most popular modeling styles and demonstrates how great models can be built using any type of notation
- Explains how to use an organization’s plans, policies, objectives, and strategies to build accurate, complete, and useful models
- Offers detailed guidance to establishing a continuous quality evaluation program that’s easy to implement and follow
- Packed with real-world examples and annotated diagrams illustrating each point covered
- Describes how to use Case tools most effectively to build high-quality models
About the Author
MICHAEL C. REINGRUBER is Technical Leader for the development of the SRA Business Reengineering Methodology. WILLIAM W. GREGORY is Deputy Director of the Business Process Improvement Division of SRA.
Most helpful customer reviews
3 of 3 people found the following review helpful.
I like this book - great for learning and review
By Jonathan Despain
I have been working with data models and databases for many years. Recently I was involved in a project to redesign a complex and important set of data structures that developers had redesigned 3 times in the last 10 years. In working on the design I noticed strong need for things like type-subtype relationships and recursive many-to-many relationships. Worried that I was going to steer the project down a dark alley I went through my home bookshelf looking for a reference that would refresh some rusty memories.
The Data Modeling Handbook was one of two books that I found. I looked at the other book first. It got a few page flips and was tossed aside. I then began flipping through Data Modeling Handbook. It turned out to be exactly what I was looking for. I spent time into the very late evening reviewing entity designs, relationships, and good and poor practices. It took a few hours but I covered 150-200 pages of material with clear examples that were pivotal in making solid design decisions and communicating them to a jaded cross-functional redesign project team.
It took another week or ten days, but the developers in that cross-functional redesign team now have a data model that meets pressing current needs and happens to solve problems originally thought unapproachable. How do they feel about the design? That formerly 'jaded' group is now excited to demonstrate (and even defend) their elegant yet practical data design to a larger group of developers.
Today I'm on Amazon to order a second copy of the Data Modeling Handbook for the DBA group bookshelf. My copy is going back home with me.
8 of 10 people found the following review helpful.
Misleading or, if you want, wrong
By VinÃcius Medina Kern
The authors deny the fifth normal form and state special-case rules as if they were universal. Examples: Eliminate triads; Two entities cannot have more than one relationship. Although in some specific situations the advice might be valid, anyone who is trying to learn from the reading will be misled. Less harmful, even interesting, for a professor (to learn how not to approach the teaching of DB modeling).
Poor, underdocumented examples. Oversimplification. Unfortunately at the time I had only the title to choose from. Good thing most books now have a table of contents.
Database modeling still doesn't have strong references as database theory does (Date's, Ramakrishnan's, Elmasri's only to cite three). There are excellent theoretical (Thalheim's "Entity-Relationship Modeling" is good) and philosophical approaches (finally they re-published Kent's opera-prima "Data and Reality", fabulous).
The picture is poor when it comes to hands-on modeling. Bruce's "Designing Quality Databases..." is an exception. Good and useful for someone who is developing modeling expertise. But I especially don't recommend Reingruber&Gregory's book.
0 of 0 people found the following review helpful.
Fundamental to Developing Strong Systems.
By E. Mintz
I have written software professionally for over fifty years. I live by the principles set forth in this book.
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