Data Model Patterns: Conventions of Thought

by David C. Hay

Book Overview

Learning the basics of a modeling technique is not the same as learning how to use and apply it. To develop a data model of an organization is to gain insights into its nature that do not come easily.... This description may be from another edition of this product.

• Format: Hardcover
• Language: English
• ISBN: 0932633293
• Release Date: January 1996
• Publisher: Dorset House
• Length: 288 Pages
• Weight: 1.60 lbs.
• Dimensions: 10.5" x 0.8" x 7.5"

Customer Reviews

Learn to think like a data modeler

I can understand why this book has gotten some mixed reviews. The author addresses many common modeling problems. But readers looking for instant solutions to those problems will probably be disappointed. Those looking for oop patterns are reading the wrong book. And anyone looking for a beginner's introduction to data modeling will be completely lost. But if you've been feeling as if your database designs could be better, but you're not sure how, you need this book. Mr. Hay covers many real-world modeling problems. His discussions of these problems give incredible insight into the thought process of a professional data modeler. That is the true value of this book. I first read this book about three years ago and now I am totally embarrassed by every database I created before. I've re-read it many times since and my copy is beaten and dog-eared. Thankfully, it's a hardcover book. Make sure you read all the footnotes in the book. Some of them are hysterically funny.

Fantastic Collection of Ideas

This books is great for getting ideas. I use it to help me think about data models that I'm creating. Hay presents his thinking from many perspectives. He's not trying to say, "Here's how you do this data model." What he does is present different aspects of modeling various subject areas; illustrating various slants at approaching models for the subject area. This is very helpful when brainstorming or trying to come up with a model. This book is a great reference that I consult consistently at the beginning of each new modeling task. A must have.

Abstract, But If You Make The Connection To Your Business...

you will not be disappointed. The models presented are, as other readers have noticed, highly abstracted, and I believe that Mr. Hay himself would agree. That said, the view he presents assists you as a data analyst with creating data models that are, in fact, more elegant and which do, in fact, more accurately represent the information you're attempting to capture. Despite having developed commercial software since I was in high school, nearly all of it with database components, this book finally gave me the higher-level understanding that I needed.As for criticisms that the book is focussed on relational database technology, for the most part, this is correct. However, as a developer, I believe that the careful business analysis that Mr Hay's approach infers is one area in which current OO practice leaves much to be desired. It doesn't matter if you're an Oracle, DB2 or Cache shop. This book will help you understand your data better.

The best I have read on the subject

I have been in Data modeling for now more than 10 years and thought I knew what I was talking about. Hay proved me wrong. Even the Universal model which I was so proud to have discovered on my own is there in almost all possible uses and combination (minus one, but I'll only share it with the VERY interested ones). I have had this book at hand for almost a year now and it is one of the few I consult almost daily. My only grudge is it is based on the Oracle methodology. But this is a very personal grudge.

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"!