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"If you and your organization want to go beyond just talking about data as one of your most valuable assets, Danette lays out clearly how to begin treating data like the one--offering the most robust, comprehensive approach to data quality found anywhere. Her years of expertise pack this book with a practical, structured methodology and necessary guidance to help any organization achieve the level of data quality necessary to thrive in the Information Age."

Douglas B. Laney, Data & Analytics Strategist, and author of Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage

 

 

 

Praise for the Second Edition

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

"If you and your organization want to go beyond just talking about data as one of your most valuable assets, Danette lays out clearly how to begin treating data like the one--offering the most robust, comprehensive approach to data quality found anywhere. Her years of expertise pack this book with a practical, structured methodology and necessary guidance to help any organization achieve the level of data quality necessary to thrive in the Information Age."

Douglas B. Laney, Data & Analytics Strategist, and author of Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage


"The need for high-quality data has never been greater! Managers need to guide their organizations, employees need to do their work, and we all need to take care of our families. All much harder in the face of a global pandemic and its consequences.  Data could be our best, most powerful weapon.  McGilvray's Ten Steps is a proven guide to help attack the underlying issues. I've been a huge fan, for a long-time, of the first edition of Executing Data Quality Projects. The second edition features terrific updates to help people and teams tackle the really important problems."

Tom Redman, the Data Doc, Data Quality Solutions


"Great books do not sit on your shelf, pristine and beautiful, without so much as a crease in them. The best books occupy precious desk space, dog-eared and highlighted. By this standard, Danette McGilvray's book, Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information™, will be absolutely ravaged, and never more than arms-length away. The power of the content and techniques she has brought into one volume is a testament to the book itself: by applying the principles covered inside, the author has assembled a collection of knowledge and tools to help readers at every point in their data quality journey. This is not a book you will read once and put on a shelf -- this will be a faithful companion guiding you daily."

Anthony J. Algmin, Founder, Algmin Data Leadership

 

"Within my field of expertise, computer security, I hadn't had much exposure to the concept of "Data Quality." Now that I've been introduced to it, however, I am convinced that data quality is essential to computer security and that security professionals will never successfully defend systems until they incorporate it into their practice. To get started, I recommend reading McGilvray's book Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information™. I literally tell people that this book changed my (professional) life. Not only did it do a great job of teaching core data quality concepts in a way that even a newbie like myself could understand, digest, and apply, but the Ten Steps themselves, the real meat of the book, are amazingly actionable. The overwhelming emphasis on practicality and contextualization creates a framework that can be used in almost every possible environment to improve an organization’s data quality."

Seth James Nielson, PhD, Founder and Chief Scientist, Crimson Vista, Inc.

 

"I've known the Ten Steps and Danette for 10 years. Through the decade, many data practitioners in China apply the method to real data quality and data governance projects and programs. By doing so, the organizations benefit from higher data quality. The Ten Steps Process itself has evolved and I believe more data, more people and more organizations will get more value from the deep thought and experience embedded in this book. The legacy of this book to the data community cannot be overstated."

Chen Liu, CEO of DGWorkshop (御数坊)

 

"If we don’t recognize that we are living in a knowledge economy in which data has significant value, it’s time we did. Yet, further research by the University of South Australia and Experience Matters on three continents shows irrefutably that data is not managed well. Amongst many other findings, its value and benefits aren’t measured. Boards and executives don’t understand why information assets are important and, unlike financial assets, nobody is held truly accountable for their management. Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information™ is a knowledgeable and pragmatic guide to managing data well. I highly recommend it for anyone who wants to make money out of their data and / or improve their service delivery. And that will be the vast majority of people reading this."

James Price, Managing Director, Experience Matters

 

"When Danette said that she was working on a second edition of Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information™, my first thought was, “Why? The first edition was so good and the process is sound.” But I am pleased to say that the second edition is even better. In the second edition, McGilvray has clarified and updated the process steps and supporting templates and incorporated valuable examples and case studies (The Ten Steps in Action), while accounting for the evolution of technology and data production over the past decade. The presentation is clear and crisp. People who are new to data quality  management should read this book cover to cover. Experienced practitioners should have it on their desks at all times for reference."

Laura Sebastian-Coleman, Author, Measuring Data Quality for Ongoing Improvement

 

"I have consistently used this book in my courses for years and I recommend this book to all of my students in the Information Quality Graduate Program at the University of Arkansas at Little Rock. Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information™ is an excellent guide for navigating the journey toward organizational data excellence. Danette McGilvray delivers an outstanding job in making a difficult topic easy. The concepts in this book are easy to understand. Her Ten Steps process and recommendations for how to apply these steps to a variety of projects are easy to follow. The techniques she showcases are easy to implement. In summary, this book is for anyone trying to find well written, practical, and effective advice for making their data great."

Dr. Elizabeth Pierce, Chair, Information Science, UA Little Rock

 

"The University of Arkansas at Little Rock Information Quality Graduate Program has been using the first edition of Executing Data Quality Projects as the textbook for our course on project and change management since 2012, and it has proved to be a tremendous resource for our students. Comprehensive and detailed, yet full of practical advice and helpful templates, it has become a “must have” book for information quality practitioners around the world. The new edition is even richer and deeper. While keeping the original foundation, it brings in new content to address the changes and emerging trends in data management and technology since the first edition. I am excited to introduce our students to the new edition."

Dr. John R. Talburt, Acxiom Chair of Information Quality, University of Arkansas at Little Rock, and Lead Consultant for Data Governance and Data Strategy, Noetic Partners

 

"Since Danette wrote the first edition of this book, the volume of data in all organizations has grown enormously. If, at this time, your organization is not investing resources into ensuring high-quality data, and managing this data as a valuable asset, you are heading for trouble. The Ten Steps methodology outlined in this book has proven an invaluable guide for both experienced data practitioners as well as those who are embarking on their own data quality journey. Furthermore, if you need to convince your executive team of the benefits of investing in high-quality data, this book is an invaluable place to start."

Peter Eales, CEO MRO Insyte, and project leader of ISO 8000-110 edition 2

 

"Whether you are a data quality professional, IT leader, data analyst, or just someone trying to solve a complex problem, Danette’s Ten Steps approach is the perfect guide to help you through the process. Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information™ can be used as a textbook, an informational read, or my preference as a “shop manual.” The updated 2nd edition helps readers navigate through modern and less structured database problems."

Andy Nash, Data Quality Professional

 

"Danette McGilvray’s Ten Steps to Quality Data took our data quality initiative from theoretical to possible. The techniques taught by Danette provided concrete and practical methods to deliver on our data quality initiative through our Data Governance Council. Showing the return on investment for a data quality initiative was always one of the most challenging endeavors for this effort. Ten Steps to Quality Data helped cultivate those ROI ideas that ultimately led to a successful and sustainable implementation."

Brett Medalen, Principal Architect, Navient

 

"As a data-driven organization, Seattle Public Utilities continually seeks to leverage best in class methodologies to manage our data. Danette McGilvray’s Ten Steps to Quality Data and Trusted Information™ is one such methodology. Robust, extensible and transparent, Danette’s methodology can be applied quickly and effectively to data quality issues as they surface. Perhaps more importantly, in this second edition, Danette illustrates how the methodology can be leveraged in the software /system development lifecycle (SDLC). Doing so leads to pro-actively managed data quality that raises the usability of an organization’s data, lowers the risk of poor decisions and outcomes and reduces costs of data management across large organizations."

Duncan Munro, Utility Asset Information Program Manager, Seattle Public Utilities

 

"The name of the book is remarkable in the extent to which it covers what the book is about. What is less clear from the name, however is the quality of the book’s content. Ms. McGilvray writes very well, and her organization is ideal for conveying a great deal of information. As she puts it, “There is just enough structure to show you how to proceed, but enough flexibility so that you can also incorporate your own knowledge, tools, and techniques.” In addition to extensive descriptions of data quality “key” concepts, the heart of the book contains instructions and guidance to carry out each of the Ten Steps, followed by how to structure your project, and other techniques and tools. It is with great pleasure that I endorse this book."

David C. Hay, Data Modeler emeritus, Essential Strategies International

 

"Tasked with designing data quality metrics for my organisation and faced with a blank piece of paper, I turned to the 2nd edition of Danette McGilvray’s book Executing Data Quality Projects. Within a short space of time I was able to utilise the information on metrics to kickstart my project – with so much more practical advice available in the 2nd edition, I would thoroughly recommend it as an upgrade to those who already have the 1st edition."

Julie Daltrey, Senior Data Architect, Intellectual Property Office, UK.

 

"McGilvray has come up with a pragmatic approach to improving data quality. This book will increase your skills, arm you with useful tools when facing data management challenges, and widen your perspectives regarding the challenges of ensuring quality data. And there are indeed challenges as everyone works with data in their daily lives and data are created everywhere by almost any kind of technology. This book will help you know where to start, who to involve or persuade, and what actions to take."

Håkan Edvinsson, author, trainer and practitioner in data governance and business data design, the inventor of the Diplomatic Data Governance approach.

 

"The second edition of Danette McGilvray’s book, Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information™, is timely and a must-read for every person and organization focusing on being data-centric. In the 13 years since her first edition arrived on the scene, data quality has become the driving force required to demonstrate a return on most, if not all, data-oriented projects and programs. From data analytics and data science, to data governance, to metadata management, to the improvement of interoperability, data quality is the primary factor used to determine success or failure. Danette’s straight-forward approach, and the practical tools and processes that she shares throughout the book, are immediately applicable to everyone’s information landscape and will quicken the pace toward achieving your organization’s goals. I highly recommend this book."

Robert S. Seiner – KIK Consulting & Educational Services (KIKconsulting.com) and The Data Administration Newsletter (TDAN.com)

 

"Danette has provided a solid methodology with easy to follow action steps that can be used today and in the future for trusted data that supports business goals and objectives. This second edition is a must have reference and guide as the importance of data quality continues to grow with enhancements in data technologies and the explosion of data."

Mary Levins, President Sierra Creek Consulting LLC

 

"I was highly impressed with Danette’s Ten Steps to Quality Data and Trusted Information™, especially as I began a data quality project to develop an ontology-driven data quality framework for biobanking research and capture clinical trial data for cancer research. The book teaches data practitioners ten simple, timely, and powerful steps to improve overall quality standards of data across the enterprise. I can see many data leaders leveraging the steps to deliver clean and trusted data across the enterprise, especially while meeting business outcomes covering insights and analytics, regulatory compliance, data literacy, and digital transformation."

Kash Mehdi - Data Governance Domain Expert, Informatica | Ph.D. Candidate Information Science, University of Arkansas at Little Rock in collaboration with MIT

"As a researcher in the field of Data and Information Management and Governance, as one of the authors of The Leader’s Data Manifesto and as strong supporter of industry/academia collaboration, I am honoured to endorse this book by Danette McGilvray. In the digital world we live in, there is an increasing need to raise awareness about the importance of data and information. An understanding of data and information quality is more relevant and critical now than ever before. As Danette suggests: “Teaching tomorrow’s leaders to be data-aware is a good place to start”. In fact, all our students need to learn why we have to manage data and information as vital assets, how to improve their quality and the resulting benefits to organisations in all industries. What strikes me most about this book is the way it can be used to bring the real world into the classroom - the templates, detailed examples, and practical advice to enhance data and information quality will be very useful for students in their future careers. I will certainly recommend this book for our Masters of IT and MBA students studying courses related to Data and Information Management, Privacy, Governance and Quality. I strongly support Danette in her mission: “Let’s continue to add data and information to the conversation…”

Associate Professor Nina Evans, Professorial lead: UniSA STEM, University of South Australia


"For the past 10 years Danette McGilvray has been the pre-eminent international expert in data quality and its improvement. Her vast experience in both teaching and consulting is evident in this book."

Michael Scofield, M.B.A. Professor 


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