A Data Quality Primer: Using Data Quality Tools and Techniques to Improve Business Value

by David Loshin, Melody Yen (Illustrator)

Over the past two decades, the conventional wisdom on data quality has changed, resulting in an altered perception of what is meant by “quality information”. Read this eBook to learn more about the challenge in understanding when data values are or are not correct; how data values can be made correct, and how data cleansing services can be integrated into the environment. Highlights of this eBook include a discussion of five key aspects of data quality data cleansing, address data quality, address standardization, data enhancement, record linkage and matching; and a look at some of the practical aspects of introducing proactive data quality management into the organization.

62 pages, Kindle Edition

First published May 29, 2012