Anyone who begins a major data quality enhancement project is likely to have high expectations for the improvements that will result. The users of the existing data will understand all its failings and will be eager to work with the enhanced quality that will result from a project. I have often heard people use words like 99.9 percent accuracy, 99.9 percent completeness or real-time data access. While these are laudable goals, they are surprisingly difficult to achieve. And it’s never been clear to me that the end users actually need these quality levels. As John Kay observed, “In a world of imperfect knowledge and irresolvable uncertainty - of unknown unknowns - the quest for exact knowledge gets in the way of useful knowledge.”1

 

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