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The Data Modeling Handbook : A Best-Practice Approach to Building Quality Data Models
 
 
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The Data Modeling Handbook : A Best-Practice Approach to Building Quality Data Models [Hardcover]

Michael C. Reingruber (Author), William W. Gregory (Author)
3.7 out of 5 stars  See all reviews (12 customer reviews)

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Book Description

0471052906 978-0471052906 December 1994 1
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

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Customers buy this book with Joe Celko's Data and Databases: Concepts in Practice (The Morgan Kaufmann Series in Data Management Systems) $49.60

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Editorial Reviews

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

Product Details

  • Hardcover: 384 pages
  • Publisher: Wiley; 1 edition (December 1994)
  • Language: English
  • ISBN-10: 0471052906
  • ISBN-13: 978-0471052906
  • Product Dimensions: 9.6 x 6.4 x 1 inches
  • Shipping Weight: 1.6 pounds (View shipping rates and policies)
  • Average Customer Review: 3.7 out of 5 stars  See all reviews (12 customer reviews)
  • Amazon Best Sellers Rank: #233,451 in Books (See Top 100 in Books)

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Customer Reviews

12 Reviews
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Average Customer Review
3.7 out of 5 stars (12 customer reviews)
 
 
 
 
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12 of 13 people found the following review helpful:
5.0 out of 5 stars Easy to understand, January 31, 2001
This review is from: The Data Modeling Handbook : A Best-Practice Approach to Building Quality Data Models (Hardcover)
I have many books on data modeling but this one is probably the most understandable. The examples are well-formed and many diagrams are provided along with written explanations. They do an excellent job of going through 5th normal form and show how to resolve many different issues such as special cases in generalization hierarchies. I have found this book very useful in practice and it has served me well.
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9 of 10 people found the following review helpful:
5.0 out of 5 stars Excellent book!, April 8, 2001
By A Customer
This review is from: The Data Modeling Handbook : A Best-Practice Approach to Building Quality Data Models (Hardcover)
This book is excellent. The subject matter is advanced but still easy to read and understand. The examples used in the book are varied and excellent illustrations of the problems discussed in the book. Many of the examples remind me of similar data modeling errors I have seen in my experience and give excellent methods of correcting the mistakes. I highly reccomend this book for the data modeler who is ready to go to the more advanced conecpts. (You must know basic data modeling concepts to understand this book, such as how to read diagrams, basic terminology, etc.)
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8 of 9 people found the following review helpful:
5.0 out of 5 stars Excellent resource for any data modeller, January 6, 1999
By A Customer
This review is from: The Data Modeling Handbook : A Best-Practice Approach to Building Quality Data Models (Hardcover)
This book is really a "no-nonsense guide" for data modeller. However the diagram conventions are significantly different than found on some of the popular CASE tools. But overall I keep refering to this book.
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Inside This Book (learn more)
First Sentence:
Before you begin to read through the rules (once you start, we're sure you won't be to stop!), we offer these thoughts: We did not get them all. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
hazardous material rating, every data model, subtype discriminator, dangling foreign key, including derived attributes, material type stock number, optional foreign key, course offering date, data model quality, employee termination date, health plan name, data administration group, data model view, aircraft tail number, modeling team, associative entities, single instance entities, associative entity, derivation dependency, discriminator attribute, metadata control, data dependency analysis, good data models, data modeler, repeating attribute
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Rosewood Invitational, Meter Run Pierce, Sun Valley Relays, Clive Finkelstein, Las Vegas, San Antonio, Examples In Figure, James Christian, Database Systems, Englewood Cliffs, Example Our, John Doe, San Diego, Strategic Systems Development, Example Assume, Example Figure, Examples Figure, New York, Workshop One
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