Since how data quality is defined has a significant impact on how data quality is perceived, measured, and managed, in this post I examine the two most prevalent perspectives on defining data quality, real-world alignment and fitness for the purpose of use, which respectively represent what I refer to as the danger of data myopia and the challenge of business relativity.
Real-World Alignment: The Danger of Data Myopia
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