Survival Guide: Taming the Data Quality Beast

As companies scramble to adjust to the demands of an increasingly data-driven world, testers are told “go test data quality” without any guidance as to what that entails or how to go about it. The fact that the data is often a living, flowing ecosystem, rather than just a single object, requires the use of different strategies to gain meaningful insights. Shauna Ayers and Catherine Cruz Agosto guide you through the challenges of data quality and apply a structured approach to analyze, measure, test, and monitor living data sets, and gauge the business impact of data quality issues. Shauna and Catherine define data quality, describe the five goals of data quality management, provide the four pillars of data quality assurance, and show how data flow, scale, and properties interact to build the data quality landscape. Learn how to tame the data quality beast, determine what and how to test, overcome technical obstacles—and emerge with a usable plan of attack.