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The Data Model Resource Book, Vol. 3: Universal Patterns for Data Modeling (Volume 3) 1st Edition

4.5 out of 5 stars 56 customer reviews
ISBN-13: 978-0470178454
ISBN-10: 0470178450
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Editorial Reviews

From the Back Cover

"Universal Patterns for Data Modeling is essential reading for anyone undertaking commercial data modeling. The Data Model Resource Book series represents the most important contribution to the data modeling discipline in the last decade."
—Dr. Graeme Simsion, author of Data Modeling Essentials and Data Modeling Theory and Practice

This third volume of the bestselling Data Model Resource Book series revolutionizes the data modeling discipline by answering the question "How can you save significant time while improving the quality of any type of data modeling effort?" In contrast to the first two volumes, this new volume focuses on the fundamental, underlying patterns that affect over 50 percent of most data modeling efforts. These patterns can be used to considerably reduce modeling time and cost, to jump-start data modeling efforts, as standards and guidelines to increase data model consistency and quality, and as an objective source against which an enterprise can evaluate data models.

For each pattern, numerous alternatives are provided, ranging from very specific to very generalized ways of modeling. Len Silverston and Paul Agnew point out the pros and cons of these alternatives and provide guidelines to help you make appropriate decisions depending on the set of circumstances faced. In developing and documenting these patterns, the authors share an invaluable set of foundational tools for anyone involved in data modeling, from the novice to the expert. The authors show you how to:

  • Model the most prevalent data modeling constructs such as ways to model roles, hierarchies, classifications, statuses, contact information, and business rules

  • Re-use a powerful library of core patterns for data modeling

  • Model at different levels of generalization

  • Evaluate the pros and cons of specific versus generalized models

  • Apply the patterns in many types of data modeling efforts, such as prototypes, applications, enterprise data models, data warehouses, and master data management efforts

  • Gain buy-in regarding the use of patterns and/or standardizing on these patterns

About the Author

Len Silverston is the best-selling author of The Data Model Resource Book (Volumes 1 and 2), a speaker and data management consultant with more than 25 years of experience helping organizations integrate their information and systems. He is the owner and president of Universal Data Models, LLC.

Paul Agnew is an author and consultant with more than 17 years of experience in the data management field in many different industries. He is an expert in data modeling, architecture, and integration. He is a senior partner at Universal Data Models, LLC (www.universaldatamodels.com).

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Product Details

  • Paperback: 648 pages
  • Publisher: Wiley; 1 edition (January 9, 2009)
  • Language: English
  • ISBN-10: 0470178450
  • ISBN-13: 978-0470178454
  • Product Dimensions: 7.4 x 1.4 x 9.3 inches
  • Shipping Weight: 2.1 pounds (View shipping rates and policies)
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (56 customer reviews)
  • Amazon Best Sellers Rank: #412,972 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

Format: Paperback
As an analyst for a large manufacturing company's ERP implementation, I was responsible for a very complex and critical area called Classifications. Classifications was the place where all products, vendors, or customers were grouped into buckets based on similar behavior. For example, if this company manufactured vehicles, there could be classifications for hybrids, sports cars, SUVs, minivans, etc. To better understand classifications, I dived into screens, help files, and actual database tables and after several weeks, completed a classifications data model. The model I produced was very similar to the data model that appears on page 224 of "The Data Model Resource Book Volume 3: Universal Patterns for Data Modeling" by Len Silverston and Paul Agnew.

This book contains a collection of patterns, which are general building blocks that could be used as the basis for just about any type of data modeling within any industry. Classifications is one example, and there are a collection of others such as roles, statuses, and contact mechanisms. Whereas Volumes 1 and 2 in The Data Model Resource Book series contained models for common business processes or industries, this volume contains patterns that cross through all processes and industries. Consistent with the series however, the purpose of this text is to save the modeler time so instead of starting from scratch, the modeler can start from a reliable and proven foundation. Realizing these patterns exist and making them work for your particular modeling assignment can result in a higher quality data model and a greater level of consistency within your organization.

A majority of the book is dedicated to chapters which describe how to model a pattern at different levels of generalization.
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Unlike the world of Object Oriented programming, there are very few pattern books devoted to data modeling. This is unfortunate because most business applications suffer from over-specialization & inflexibility in the data model, where change is very expensive. The few data model patterns books that do exist do not explore the depths of subject to the extent that this book does.

Based on their many years of experience, Silverston & Agnew chose to focus on the most common areas of interest (Parties, Roles, Relationships, Statuses, Classifications, Contact Mechanisms, & Rules) and offer a set of data model pattens for each. Each area has a set of "pattern levels" ranging from specific to general, listing benefits, drawbacks, & usage guidelines for each. The modeler can choose which pattern level best suites the enterprise based on perceived needs.

This book can be thought of as the "gang of four" book for data modeling. I would recommend this book for anyone engaging in any form of data modeling. You may not use the exact patterns, but it will at least serve as a catalyst for future thought.
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The text of this book was generally good - although it seemed padded out with a massive listing of model metadata. The book comes with a CD. The first surprise was, the CD does not include the Data Definition Language (DDL) for its sample models... there's an extra cost for that. My question to the publisher would be, what good is the CD you provide for free?

The second surprise is the illustrations. There are plenty of them, but they look like they were done in a primitive graphics package - not in an enterprise modeling tool. They author seems to have invented his own wierd set of conventions, including "foreign keys do not appear in the entities... that is duplicate information". Before you buy this book, take a look at the illustrations of the models. If you can live with the notation, maybe consider buying it.
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Format: Paperback
I got both the volumes 2 years back. I found the concepts really useful and have applied the modeling constructs to actual engagements in supply chain, corporate banking and travel industry. Especially the "party-role-transaction" construct . It is truly a liberating data modeling construct to apply across industry. The models are also at the right level of abstraction. It elegantly positioned in between 2 modeling extremes ... It is neither too abstract/conceptual nor too specific and detailed to one implementation ... a balance which is typically very difficult to maintain . One word of caution on expectation ... the objective is to treat these models as a starting point for your specific projects. It need not be the only way to model a business scenario. But the book opens the modelers mind upto possibilities which one typically tends to ignore and that is the key! Because often times these "outlier scenarios" tend to come and haunt the architecture once realized physically on a database and is often a painful process to modify. Lens varied experience highlights some specific "land mines" to watch for in modeling these scenarios which has helped me in my projects. In a nut shell I have found the book to express in a concise manner the essential elements of modeling to watch out for
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Format: Paperback
The Data Model Resource Book is as important to a data modeler or application developer as a dictionary is to a writer: you're not at your best without it. Where I've worked, this material has helped me create the architecture for an enterprise data model of our company. Aided by the Resource Book, we build a framework of major tables containing subject areas and the result is a business model to which we can map all of our application databases and data warehouses.
This book is basically rather simple to use; you find the data or subject of interest and then check to see if there are any attributes or relationships in the book that are relevant to your specific application database. This type of a check helps add quality and completeness to your logical and physical model.
But using the book just scratches the surface of its value; it's the author who's responsible for its quality and completeness. I've personally worked with Mr. Silverston who participated in consulting engagements at our firm and I`ve also seen him perform in the classroom setting. He seems to have an uncanny ability to analyze a given business situation-no matter how seemingly bizarre-and to create a model structure that will accommodate any situation.
I highly recommend the Resource Book to business analysts, application developers, programmers, and data warehouse designers.
Ted Kowalski Data Architect, Equilon Enterprises, Houston and author of "Opening Doors--A Facilitator's Handbook."
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