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IAIDQ Publications

A Long, Strange Trip Ahead: Process Management and Data Quality
July 2010
Thomas C. Redman

I've had the good fortune to work with dozens, maybe even hundreds, of organizations on their data quality programs over the past two decades. Experience has shown that poor data quality has been, and is, the norm. Time and again, we've found data that are incorrect (inaccurate), out-of-date, poorly defined, not relevant to the task at hand, difficult to interpret, and otherwise unfit for use.

In almost every situation, one or both of the following was a root cause (and often the most important root cause) of poor data quality:

  • Data creators. i.e., sources of data. did not understand the needs or requirements of important data customers, or
  • Data customers, i.e., those who put the data to use in operations, decision-making, or planning, did not understand what the data meant.

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