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

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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.

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Editorial Reviews

From the Publisher
My esteemed colleague describes a practical approach for planning and managing information quality. I recommend you read, understand, and apply the learnings found here.
- Larry P. English, President and Principal, Information Impact International, creator of the TIQM Quality System. Conceiver and co-Founder of the International Association for Information and Data Quality

In a subject that is long on talk and short on practical advice for implementation, Danette McGilvray is a refreshing exception. If you want to know HOW to execute data quality projects, read this book — everything you need to know is in here.
- David Plotkin, Data Quality Manager, California State Automobile Association

This book is a gem. Tested, validated and polished over a distinguished career as a practitioner and consultant, Danette's Ten Steps methodology shines as a unique and much needed contribution to the information quality discipline. This practical and insightful book will quickly become the reference of choice for all those leading or participating in information quality improvement projects. Experienced project managers will use it to update and deepen their knowledge, new ones will use it as a roadmap to quickly become effective. Managers in organizations that have embraced generic improvement methodologies such as six sigma, lean or have developed internal ones would be wise to hand this book to their Black Belts and other improvement leaders.
- C. Lwanga Yonke, Information Quality Practitioner.

Danette’s book takes a pragmatic and practical approach to achieving the desired state of data quality within an organization. It is a "must-read" for any organization starting out on the road to data quality.
– Susan Stewart Goubeaux, Director, Business Intelligence, FHLBanks Office of Finance

"Data quality" has become one of those hackneyed phrases in our industry that everyone supports, but only a few organizations have achieved to the degree they need to move forward in their industries. What is required is a guide to explain to the business people who want better data just how to get it. This book is just such a guide. While the individual steps should not be a great surprise, her organization makes them immediately actionable to a degree previous books have not. In short, this is definitely required reading for anyone embarking on a data quality project.
– David Hay, President, Essential Strategies

Danette has taken what has previously been presented in the abstract and made an excellent, concrete guide toward improving data quality.
– John Ladley, President of IMCue Solutions

Using this methodology, you will never lose your way on your data quality project! This book is peppered with tips, guidelines, templates, cross-references, and call-out icons. Plus, there are many easy-to-follow examples for the most common types of data quality projects.
– Larissa T. Moss, President, Method Focus Inc.

This book presents a valuable reference for not just data professionals, but also project managers and business representatives interested in or responsible for establishing, maintaining, and/or improving data and information quality. What sets this book apart from others in the field is the business impact-driven approach to assessing and improving data quality, and the specific steps and techniques it provides every step of the way.
– Mehmet Orun, Senior Manager / Principal Architect, Data Services CoE, Fortune 250 Company

"Comprehensive" is the first word I would use to describe this book. It addresses so many nuances of every aspect of data quality assessment and improvement—-things that would go unmentioned by more superficial treatments. Bravo!
– Michael Scofield, Manager, Data Asset Development, ESRI, Inc.

This book is a "must-own" for business and technical data quality managers and practitioners. Danette clearly demonstrates where her process will add value to quality projects that stand-alone or as the backbone of a successful data integration effort.
– Robert S. Seiner, KIK Consulting & Educational Services, LLC, The Data Administration Newsletter, LLC

Danette's writing style is appropriate for her audience, the content is superb, and her Ten Steps approach is clear, easy to follow but comprehensive. This is an excellent book and I would think it will be an essential reference for any effort in data quality.
– Anne Marie Smith, PhD., Director of Education and Principal Consultant, EWSolutions, Inc.

Danette has compiled a valuable toolkit for managing information quality improvement projects. Her clear, concise definitions of concepts also make it a nice primer on the principles of information quality for data professionals, business managers, or students. I would recommend this practical handbook to anyone embarking on an information quality project.
– Eva Smith, MSIM, CCP, CDMP, Instructor, Computer Information Systems

No two data quality projects are the same. Some are large efforts focused entirely on improving some quality aspect of information. Others are subprojects within other efforts, such as a data migration. Still others are led by a few individuals trying to make a difference as they perform their everyday activities. What I like about McGilvray's Ten Steps approach is that it can serve any of these situations. This book provides a structured, easy-to-understand, and easy-to-govern methodology that you can apply to the degree that is appropriate for you.
– Gwen Thomas, President, The Data Governance Institute

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Product Details

  • ISBN-13: 9780123743695
  • Publisher: Elsevier Science
  • Publication date: 7/11/2008
  • Edition description: New Edition
  • Pages: 352
  • Sales rank: 1,126,408
  • Product dimensions: 8.40 (w) x 10.90 (h) x 0.90 (d)

Meet the Author

Danette McGilvray is president and principle of Granite Falls Consulting, Inc., a firm specializing in information and data quality management to support key business processes around customer satisfaction, decision support, supply chain management, and operational excellence.

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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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Customer Reviews

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Sort by: Showing 1 – 3 of 4 Customer Reviews
  • Anonymous

    Posted March 19, 2013

    Shelbu

    Thanx. Goin to bed now. Goodnight^_^

    Was this review helpful? Yes  No   Report this review
  • Anonymous

    Posted September 2, 2008

    Welcome Addition

    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.

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  • Anonymous

    Posted June 23, 2008

    A useful, practical guide for data intensive projects

    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.

    Was this review helpful? Yes  No   Report this review
Sort by: Showing 1 – 3 of 4 Customer Reviews

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