For the data industry, standardized definitions of data quality dimensions are needed, just as other professions, such as accounting have agreed-upon concepts and terms like “chart of accounts”. It is then up to each organization to gain competitive advantage by the way the dimensions are applied (through assessments, root cause analysis, improvements, metrics, etc.) to manage and increase the quality of the information and data on which the organization depends.
About Dan's book, Data Quality Techniques:
“Dan Myers and I are both proponents of using data quality dimensions to measure and manage various characteristics of data. This book dives deep into those dimensions with definitions, underlying concepts, and how to measure them- yet it is practical and easy to read. It reflects Dan’s years of experience and he shares details that will help any practitioner who is responsible for measuring and managing data quality. Learn from this book, put it to use, and keep it on your shelf for continued reference. You will be glad you did!”
-Danette McGilvray, renowned data quality expert and author of Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information™