“Dan Myers’ book Data Quality Techniques is a well-written and much needed text for data professionals and students alike. All too often, data quality concepts are discussed assuming that the reader can easily understand and correctly apply them. However, in both my academic and professional practice I find this not to be the case. This is why I am especially impressed with how each data quality concept presented in this book is also illuminated with understandable, practical examples. I am also impressed with the comprehensiveness and the level of detail in this book. While there have been many good books addressing various aspects of data quality, this book is noteworthy for its breadth of coverage. It goes far beyond basic dimensions, error types, and metrics to provide practical insights on data quality management methodologies, auditing methods, the intersection with data governance, the importance of data contracts, and many other topics critical to data quality management success. The new age of artificial intelligence has brought a sharp focus on data quality. I highly recommend this book to anyone trying to understand how good data quality management practices can add value to an organization.”
-John Talburt, Professor of Information Science, University of Arkansas at Little Rock