Data Model Patterns: A Metadata Map not only presents a conceptual model of a metadata repository but also demonstrates a true enterprise data model of the information technology industry itself. It provides a step-by-step description of the model and is organized so that different readers can benefit from different parts. It offers a view of the world being addressed by all the techniques, methods, and tools of the information processing industry (for example, object-oriented design, CASE, business process re-engineering, etc.) and presents several concepts that need to be addressed by such tools. This book is pertinent, with companies and government agencies realizing that the data they use represent a significant corporate resource recognize the need to integrate data that has traditionally only been available from disparate sources. An important component of this integration is management of the "metadata" that describe, catalogue, and provide access to the various forms of underlying business data. The "metadata repository" is essential to keep track of the various physical components of these systems and their semantics. The book is ideal for data management professionals, data modeling and design professionals, and data warehouse and database repository designers.
Reviews
"A very ambitious undertaking, masterfully described. To the best of my knowledge, this is the first published version of the detailed models implied by the Zachman Framework. David Hay builds the models one step at a time, describing in each increment why the new entities were added, and how they related to the rest of the model. At least as important he sprinkles in lessons learned from his vast experience modeling in various other industries." --Dave McComb, President, Semantic Arts, and author of Semantics in Business Systems "Dave Hay's latest book provides detailed metaschemas for the main concepts underlying the Zachman Framework for Enterprise Architecture, incorporating recent proposals from the Business Rules Group. By covering this vast territory in an easy-to-read style, Dave provides a valuable resource that should be of interest to data modeling professionals." --Terry Halpin, Neumont University



Book Information
ISBN 9780120887989
Author David C. Hay
Format Hardback
Page Count 432
Imprint Morgan Kaufmann Publishers In
Publisher Elsevier Science & Technology
Weight(grams) 860g