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Review by David Haertzen

Reading this book reminds me why I am a big Steve Hoberman fan. Here you will find an excellent introduction and summary of Data Modeling. It provides core material that is essential for beginners as well as experienced professionals. The book provides tutorials, detailed examples, and reference materials. Tutorials show how to get tasks done. A question and answer format, focuses on the key issues of data modeling and data definition such as:

  • What is a data model?
  • What are entities?
  • What is a subject area model?

Experts have added insights in critical areas. This improves the value delivered by the book.

  • Graeme Simsion authored the chapter about Working with Others
  • Bill Inmon writes about unstructured data
  • Michael Blaha writes about UML

I found a section that describes how to develop effective definitions very helpful. Examples reinforce the tutorials and show how to use techniques for real world results. Information is presented in an with numerous examples and illustrations that makes it very easy to use.

This 350 plus page book leads the reader from basic to advanced topics. The first several chapters provide key concepts and show the reader the basic elements of data modeling. After that, method chapters show how to:

  • normalize data models
  • build the data model appropriate to the audience
  • validate data models

Creating high quality data models is critical. Steve presents his Data Model Scorecard(R) approach. Data models are evaluated on ten criteria.

If you are want to learn Data Modeling or update your Data Modeling knowledge this book is excellent.


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