This white paper by David Loshin from Knowledge Integrity examines how to measure data quality and what to do when the data does not meet the level of acceptability. When a data quality service level agreement is in place, when issues are logged in a data quality incident tracking system, and when the individuals specified in the data quality service level agreement are charged with diagnosis and remediation, the result can be functioning operational data governance and the continuous monitoring and control of the quality of organizational data.

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