About "Executing Data Quality Projects"

Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information™ (Morgan Kaufman, 2008) by Danette McGilvray was published in 2008.  The second edition of this book was released in 2021. See https://www.gfalls.com/2nd-edition-2021/ for more information about the second edition.

Downloads from the first edition are available below.

In today’s world of instant global communication and trends that turn on a dime, up-to-date and reliable information is essential to effective competition.

Executing Data Quality Projects:  Ten Steps to Quality Data and Trusted Information™, provides a systematic approach for improving and creating data and information quality within any organization.

This is not just a book. It is a "How To" manual. Danette's book fills a real gap in the Data Quality literature.

- Andrew Wynn, Information Management Professional

It delivers a methodology that combines a conceptual framework for understanding information quality with the techniques, tools, and instructions for improving and creating information quality.

Every company is different, yet the underlying approach to data quality described in the book applies to all types of data, whether finance, research, development, procurement, manufacturing, sales and marketing, order management, human resources, and so on.

It applies to numerous types of organizations—businesses and corporations of all sizes, educational institutions, healthcare, government agencies, and nonprofit and charitable organizations—because all depend on information to succeed.

Content Highlights:

  • 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. 

Download the following files for easy reference to important concepts and templates for jumpstarting your information quality work.

Quick References

All Quick Reference Downloads

Individual Downloads

Templates

Individual Downloads

Important note: Information in these documents is provided "as is" without warranty of any kind, either express or implied. Every effort has been made to ensure accuracy and conformance to standards accepted at the time of publication. The user assumes the entire risk as to the use of this document. This document may be copied and distributed subject to the following conditions: 

  1. All text must be copied without modification and all pages must be included;
  2. All copies must contain the appropriate copyright notice and any other notices provided therein; and
  3. This document may not be distributed for profit.

Praise for "Executing Data Quality Projects"

Current Average Review on Amazon:

"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

"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." 

- Tom Redman, author of "Data Quality: The Field Guide" and "Data Driven" 

"As an Enterprise DQ Operations Manager, "Executing Data Quality Projects" is a must that details the "how to" methodology to execute data remediation projects. Following the "Ten Steps" methodology provides guidance on a step by step approach to establish trusted information. I used the material to create an Enterprise Level Data Quality Operations plan that was very well recieved by senior management. Danette's book is easy to follow and excellent reference material for data quality. I highly recommend it to any DQ manager, Operations Manager, etc. in any industry."

- Daniel Bucosky, Enterprise Data Quality and Metadata Management Head  

"This book is one of the most effective publications available on the topic of data quality to date. I use the word "effective” because one of the many lessons one takes  from the book is of delivering what you can, with the resources and finances at your disposal using a straightforward approach that can be easily communicated. By adopting the lessons presented in "Ten Steps" I believe that all data quality professionals will find this publication beneficial in helping take their career or business to the next level."

- Dylan Jones, Community Leader and Founder of Data Quality Pro.com 

"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

"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

"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 

"This is not just a book. It is a "How To" manual. Danette's book fills a real gap in the Data Quality literature. If you want to improve your company's data quality management practices through excellence in executing data quality projects, there is nothing else you can read that is quite as practical and hands-on."

- Andrew Wynn, Experienced Pharma Information Management and Business Analytics Professional

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