Section 4. Applying the DQAF to Data Requirements

“Whether you can observe a thing or not depends on the theory which you use. It is the theory which decides what can be observed.”

—Albert Einstein, 1879–1955

Data quality measurement requires defining the characteristics of high-quality data and assessing data against these characteristics. The process of defining specific quality metrics involves understanding data content, including the relative criticality of different data elements and rules, identifying business expectations related to data use, and assessing processes for risks to data. DQAF measurement types describe different ways to measure data completeness, timeliness, validity, consistency, and integrity. The assessment scenarios ...

Get Measuring Data Quality for Ongoing Improvement now with O’Reilly online learning.

O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.