The Data Model Resource Book: A Library of Logical and Data Warehouse Models

by Len Silverston, William H. Inmon, W. H. Inmon, et al.

Book Overview

Proven data models that save companies' time and money developing data architectures, databases and data warehouses. The Data Model Resource Book provides a common set of data models for specific... This description may be from another edition of this product.

• Format: Paperback
• Language: English
• ISBN: 0471153648
• ISBN13: 9780471153641
• Release Date: April 1997
• Publisher: Wiley
• Length: 368 Pages
• Weight: 1.45 lbs.
• Dimensions: 0.8" x 7.5" x 9.2"

Customer Reviews

For when you wonder, how should I model that....

This book provides excellent starting points for modeling basic business functions. I have found when modeling that it helps to ask another DBA's opinion on how they would aproach the same business process or data segment. This book serves as that second person. It provides proven models that can be effective for your own modeling activities. It is well worth the investment and then some.

My Bible For The Most Flexible Way To Solve Problems

I purchased this book several years ago, and while I have other goodreferences on modeling, and other books with the Inmon name on them, I mustsay this is the book that is highlighted, annotated, and worn.The sample relationships set forth in this text are so exhaustively thoughtout that I seldom find a real-world circumstance that the model won'thandle.Perhaps my favorite thing about this text is that the authors reason aloudabout their motives for creating things in a particular fashion... sowhether you agree or not, at least you understand the what and why behindthe decision... very helpful when you're considering an alternate solution.This book doesn't spell out relationships... it thinks them out.If you're someone who needs to understand the reasoning beneath the doing,someone who needs to be able to articulate your modeling decisions... thenhere's your book.€ÿ

Fantastic Resource for Launching Business Data Models

The most difficult part of creating a business data model is recognizing and correctly identifying the entities of the business and the true relationships that connect them. Do this part wrong, and the rest of your design and programming effort will suffer immensely. Get it right, and the rest will come easy. This book gives you a tremendous jump start on the modeling task. Rather than trying to describe how to do it, this book works through the actual development of many of the most commonly encountered business data models. Not only are business entities identified and classified, but the complex relationships that most information systems need to address are modeled clearly and concisely.Whether you use the templates as presented or just use them as a basis in your own modeling efforts, you should find this book a great resource. I wish something like this had been available years ago.

Excellent resource of data models and physical designs

The Resource Book is one of the more useful books I have seen on data architecture. It is just what it says: an (excellent) resource library for seven logical data models, one warehouse design, and two data mart designs. These data models and designs can be used as templates or starting points for your own modeling, an introduction to subject areas you might not be familiar with, validating your existing models, and a help to building a corporate data model. The logical models tend to be very complete. You probably won't need all their features, but they provide a good reference. The book provides a good notation for showing the relationship among high-level models, mid-level models, and data warehouse and data mart designs. Instance tables (sample data) help bring the models to life. The book also provides a good methodology for transforming logical data models to data warehouse designs. The book is an extremely useful resource.

An excellent data model reference book.

I found this book to be well written and a reflection of a vast amount of data modeling experience. The book provides insight into a number of very good data modeling techniques and provides enough detail to enable substantial productivity benefits over developing a data model from scratch. I see this book as an excellent reference for anyone needing to develop a data model as a part of any system development activity, including data warehousing. I agree however with the other reviewers of this book that star schema design is a critical component of most data warehousing solutions and that if your developing a data mart solution that Ralph Kimball's "Data Warehouse Toolkit" is an excellent book to buy as well.