ovide the business or IT professional with a practical working knowledge of data modeling concepts and best practices. This book is written in a conversational style that encourages you to read it from start to finish and master these ten objectives:

1. Know when a data model is needed and which type of data model is most effective for each situation
2. Read a data model of any size and complexity with the same confidence as reading a book
3. Build a fully normalized relational data model, as well as an easily navigatable dimensional model
4. Apply techniques to turn a logical data model into an efficient physical design
5. Leverage several templates to make requirements gathering more efficient and accurate
6. Explain all ten categories of the Data Model Scorecard
7. Learn strategies to improve your working relationships with others
8. Appreciate the impact unstructured data has, and will have, on our data modeling deliverables
9. Learn basic UML concepts
10. Put data modeling in context with XML, metadata, and agile development

Book Review by Johnny Gay
In this book review, I address each section in the book and provide what I found most valuable as a data modeler. I compare, as I go, how the book's structure eases the new data modeler into the subject much like an instructor might ease a beginning swimmer into the pool.

This book begins like a Dan Brown novel. It even starts out with the protagonist, our favorite data modeler, lost on a dark road somewhere in France. In this case, what saves him isn't a cipher, but of all things, something that's very much like a data model in the form of a map! The author deems they are both way-finding tools.