ISBN-10:
0471111759
ISBN-13:
9780471111757
Pub. Date:
12/21/2001
Publisher:
Wiley
Data Modeler's Workbench: Tools and Techniques for Analysis and Design / Edition 1

Data Modeler's Workbench: Tools and Techniques for Analysis and Design / Edition 1

by Steve Hoberman

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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.

Product Details

ISBN-13: 9780471111757
Publisher: Wiley
Publication date: 12/21/2001
Pages: 496
Product dimensions: 7.52(w) x 9.20(h) x 1.07(d)

About the Author

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.

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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