Data Modeler's Workbench: Tools and Techniques for Analysis and Design

Author:   Steve Hoberman
Publisher:   John Wiley & Sons Inc
ISBN:  

9780471111757


Pages:   496
Publication Date:   14 January 2002
Format:   Paperback
Availability:   Out of print, replaced by POD   Availability explained
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Data Modeler's Workbench: Tools and Techniques for Analysis and Design


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Overview

A goldmine of valuable tools for data modelers! Data modelers render raw data-names, addresses, and sales totals, for instance-into information such as customer profiles and seasonal buying patterns that can be used for making critical business decisions. This book brings together thirty of the most effective tools for solving common modeling problems. The author provides an example of each tool and describes what it is, why it is needed, and how it is generally used to model data for both databases and data warehouses, along with tips and warnings. Blank sample copies of all worksheets and checklists described are provided in an appendix. Companion Web site features updates on the latest tools and techniques, plus links to related sites offering automated tools.

Full Product Details

Author:   Steve Hoberman
Publisher:   John Wiley & Sons Inc
Imprint:   John Wiley & Sons Inc
Dimensions:   Width: 19.10cm , Height: 2.70cm , Length: 23.40cm
Weight:   0.862kg
ISBN:  

9780471111757


ISBN 10:   0471111759
Pages:   496
Publication Date:   14 January 2002
Audience:   College/higher education ,  Professional and scholarly ,  General/trade ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Out of Print
Availability:   Out of print, replaced by POD   Availability explained
We will order this item for you from a manufatured on demand supplier.

Table of Contents

Foreword Introduction Acknowledgments PART 1: BUILDING THE FOUNDATION Chapter 1 Using Anecdotes, Analogies, and Presentations to Illustrate Data Modeling Concepts Chapter 2 Meta Data Bingo Chapter 3 Ensuring High-Quality Definitions Chapter 4 Project Planning for the Data Modeler PART 2: ANALYZING THE REQUIREMENTS Chapter 5 Subject Area Analysis Chapter 6 Subject Area Modeling Chapter 7 Logical Data Analysis PART 3: MODELING THE REQUIREMENTS AND SOME ADVICE Chapter 8 The Normalization Hike and Denormalization Survival Guide Chapter 9 The Abstraction Safety Guide and Components Chapter 10 Data Model Beauty Tips Chapter 11 Planning a Long and Prosperous Career in Data Modeling Suggested Reading Index

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Author Information

STEVE HOBERMAN is the Lead Data Warehouse Developer for Mars, Inc. He has been data modeling since 1990 for the telecommunications, financial, and manufacturing industries. He speaks regularly at The Data Warehousing Institute conferences on advanced data modeling.

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