Scanning any CIO’s yearly list of business imperatives, it would not be a surprise to see “improving data quality” somewhere among the top 10. However, because of the hurdles in justifying an investment in data management best practices, data quality seems to suffer from a perennial lack of funding.
Linking data errors to negative business impacts helps to highlight ways that improving data quality will improve the business as well. If poor data quality impedes the achievement of desired business objectives, then being able to identify “low-hanging fruit” improvements will help to provide immediate benefits and contribute to a strategic plan for data quality management.
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