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.
Product Identifiers
Publisher
Wiley & Sons, Incorporated, John
ISBN-10
0471111759
ISBN-13
9780471111757
eBay Product ID (ePID)
1935066
Product Key Features
Number of Pages
496 Pages
Language
English
Publication Name
Data Modeler's Workbench : Tools and Techniques for Analysis and Design
Publication Year
2001
Subject
Programming / General, Data Modeling & Design, Databases / General, Information Technology
Type
Textbook
Subject Area
Computers
Author
Steve Hoberman
Format
Trade Paperback
Dimensions
Item Height
1.1 in
Item Weight
30.5 Oz
Item Length
9.2 in
Item Width
7.5 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
2001-046562
Dewey Edition
21
Illustrated
Yes
Dewey Decimal
005.74
Lc Classification Number
Qa76.9.D26h62 2002
Table of Content
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