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Best Practices for Implementing Data Quality Metrics
July 2011
Walter Howard
Data quality impacts organizations of all sizes. To address these issues, companies have started implementing functional changes in their organization’s structure to focus on data quality problems. New groups are now appearing more frequently, including Data Governance and Data Quality teams.
Noticeably missing from these campaigns to improve data quality, however, are business intelligence (BI) initiatives to proactively identify, monitor, and improve data quality errors. Simply stated, a company cannot measure the true cost of data quality or understand the extent of data quality problems without reliable data quality metrics in place.