Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information (TM)

Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information (TM)

5.0 4
by Danette McGilvray
     
 

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ISBN-10: 0123743699

ISBN-13: 9780123743695

Pub. Date: 07/11/2008

Publisher: Elsevier Science

Information is currency. In today’s world of instant global communication and rapidly changing trends, up-to-date and reliable information is essential to effective competition. Recent studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among

Overview

Information is currency. In today’s world of instant global communication and rapidly changing trends, up-to-date and reliable information is essential to effective competition. Recent studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions.

In Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information, Danette McGilvray presents a systematic, proven approach to improving and creating data and information quality within the enterprise. She describes a methodology that combines a conceptual framework for understanding information quality with the tools, techniques, and instructions for improving and creating information quality. Her trademarked "Ten Steps" approach applies to all types of data and to all types of organizations.

• Includes numerous templates, detailed examples, and practical advice for executing every step of The Ten Steps approach.
• Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices.
• A companion Web site includes links to numerous data quality resources, including many of the planning and information-gathering templates featured in the text, quick summaries of key ideas from The Ten Step methodology, and other tools and information that is available online.

Product Details

ISBN-13:
9780123743695
Publisher:
Elsevier Science
Publication date:
07/11/2008
Edition description:
New Edition
Pages:
352
Product dimensions:
8.40(w) x 10.90(h) x 0.90(d)

Table of Contents

Introduction
The Reason for This Book
Intended Audiences
Structure of This Book
How to Use This Book
Acknowledgements

Chapter 1 Overview
Impact of Information and Data Quality
About the Methodology
Approaches to Data Quality in Projects
Engaging Management

Chapter 2 Key Concepts
Introduction
Framework for Information Quality (FIQ)
Information Life Cycle
Data Quality Dimensions
Business Impact Techniques
Data Categories
Data Specifications
Data Governance and Stewardship
The Information and Data Quality Improvement Cycle
The Ten Steps™ Process
Best Practices and Guidelines

Chapter 3 The Ten Steps
1. Define Business Need and Approach
2. Analyze Information Environment
3. Assess Data Quality
4. Assess Business Impact
5. Identify Root Causes
6. Develop Improvement Plans
7. Prevent Future Data Errors
8. Correct Current Data Errors
9. Implement Controls
10. Communicate Actions and Results

Chapter 4 Structuring Your Project
Projects and The Ten Steps
Data Quality Project Roles
Project Timing

Chapter 5 Other Techniques and Tools
Introduction
Information Life Cycle Approaches
Capture Data
Analyze and Document Results
Metrics
Data Quality Tools
The Ten Steps and Six Sigma

Chapter 6 A Few Final Words

Appendix Quick References
Framework for Information Quality
POSMAD Interaction Matrix Detail
POSMAD Phases and Activities
Data Quality Dimensions
Business Impact Techniques
The Ten Steps™ Overview
Definitions of Data Categories

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Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information (TM) 5 out of 5 based on 0 ratings. 4 reviews.
Anonymous More than 1 year ago
Ill go out with u agin?
Anonymous More than 1 year ago
Thanx. Goin to bed now. Goodnight^_^
Guest More than 1 year ago
Danette McGilvray¿s new book is a welcome addition to the data quality literature. Finding and eliminating root causes of data errors is essential to any data program. And most people ¿learn quality improvement by doing,¿ following step-by-step instructions¿much as someone just learning to cook sticks close to the recipe. McGilvray does an excellent job of putting quality improvement in context and narrowing her focus. Make no mistake. This book is specially written for project managers, who must lead improvement teams over often-confusing terrain, and for team members who must do the work. This book is clearly written. It is richly detailed and chock full of templates that will help project teams move rapidly. It gets my heartiest endorsement.
Guest More than 1 year ago
This book is a valuable reference for not just the data professionals, but also project managers and business representatives interested in or responsible for establishing, maintaining, or improving data and information quality. What sets this book apart from others in the field is the specific, business-impact driven approach to assessing and improving data quality, and the practical steps and techniques it provides every step of the way.