Data Model Patterns: Conventions of Thought
Author: David C. Hay, Richard Barker
List Price: $39.95
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ISBN: 0932633293
Publisher: Dorset House (January, 1996)
Sales Rank: 39,738
Average Customer Rating: 4.31 out of 5
Customer Reviews
Rating: 5 out of 5
Data Model Design: Going from theory to implementation
For years, I searched for a book that would bridge the gap between the theoretical principles of relational database design and the actual application of those principles to a real-world problem; a reference with practical, industry-specific examples of complete data models. David Hay's book is that, and much more. Data Model Patterns provides models for specific enterprise "types". But it goes a step further by generalizing many common entities and relationships to emphasize that, although details differ, there are striking similarities between analogous data structures across enterprises. Along the way, he points out some of the more common mistakes in data model design and how to avoid them (e.g. building "relationship" information into the structure of an entity or failing to recognize the distinction between the existance of an entity and the actual use of that entity). This book is packed with diagrams, descriptions, and analysis tips. It's contribution to my understanding of data model analysis and design is nothing less than transcendental. David, you should rename this book "Zen and the Art of Data Model Patterns"!
Rating: 5 out of 5
Data Modeling Nirvana
Tour de force! This book is up there with Gamma et al's "Design Patterns" and Booch's "Object-Oriented Design" for helping me to achieve a breakthrough understanding of--in this case--database-oriented data models. Hays walks the reader through all the important domains of business--people, assets, accounting, contracts, document management, projects--and builds a concrete data model of each domain. As he proceeds through each model he draws comparisons to the previous ones revealing patterns common to all the domains. In the last chapter he summarizes the patterns and build a universal data model that applies to all domains. I believe this book can be very helpful in the development of data models in any field for two reasons. One, you can view the domain you are dealing with as a variation on one or more of the domains he presents and apply elements to your situation. Two, you can view your domain under the more abstract concepts that cut across all the domains. It's the combination and synthesis of both these elements that makes the book powerful and led me to a few moments of data modeling nivrana.This book won't help you to make tough physical database design decisions, but it may be indispensable to understanding the prerequisite analysis.
Rating: 2 out of 5
Not Practical
This book provides you with patterns for creating conceptual data models. It's not practical, though, in that it does not provide insight into how to go from conceptual to real. In fact, it's almost useless.These "patterns" are nothing more than concepts that good data modelers instinctively know already.
Also, his ER modeling techniques are a bit outdated.
Finally, this book is very, very dense and difficult to read. He just describes how to set up the models in very dense language, without going into the why's. It becomes virtually unreadable after the second or third pattern.
There are other, more recent books out there which provide better, more up to date thinking on this nascent topic (which I believe is still years, if not decades away from truly practical modeling/process techniques).
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