

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 (58 customer reviews)
Best Sellers Rank: #483,385 in Books (See Top 100 in Books) #100 in Books > Computers & Technology > Computer Science > Computer Simulation #152 in Books > Computers & Technology > Computer Science > Information Theory #162 in Books > Computers & Technology > Databases & Big Data > Data Warehousing

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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