Dan Myers: Practical Data Quality Techniques, Kartoniert / Broschiert

Klappentext

Poor quality data leads to wasted resources, missed opportunities, regulatory risks, lost revenue and tons of times fixing, cleaning and manipulating data. Sorting data quality issues before they impact your business is key to ensuring the success of your organization.

Practical Data Quality Techniques is a practical guide to building up data quality initiatives that will help drive the long-term success of any organization. In this book, mid-career data professionals will learn how to use the Conformed Dimensions of Data Quality framework to define data quality, communicate expectations in a measurable way and track improvements. Including a high-level overview of the dimensions of data quality, the book dives into the key techniques that will help transform disorganized and poor-quality data from a liability into a strategic advantage.

This book highlights numerous key data quality management techniques. It will show the skills data professionals will need to validate data quality, as well as highlights methods for profiling data and techniques to improve consistency. Explaining the role of data governance in data quality projects, it also examines the future of data quality in the age of AI. Practical Data Quality Techniques features practical real-world examples from organizations in the IT, insurance and health care industries who are getting data quality right.