David C. Hay 
Data Model Patterns: A Metadata Map [PDF ebook] 

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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. – A comprehensive work based on the Zachman Framework for information architecture encompassing the Business Owner’s, Architect’s, and Designer’s views, for all columns (data, activities, locations, people, timing, and motivation)- Provides a step-by-step description of model and is organized so that different readers can benefit from different parts- Provides 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.)- Presents many concepts that are not currently being addressed by such tools and should be

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Limba Engleză ● Format PDF ● ISBN 9780080477039 ● Editura Elsevier Science ● Publicat 2010 ● Descărcabil 6 ori ● Valută EUR ● ID 2257974 ● Protecție împotriva copiilor Adobe DRM
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