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Organizations who are serious about improving the ability to deliver critical business initiatives and ensuring that the quality of their data supports those initiatives are turning more and more to a rigorous, repeatable process for analyzing the quality of their data and taking steps to not only improve the quality of that data, but to protect that quality going forward. This effort involves not only understanding where the data quality issues exist, but also the root cause of the issues and which issues cause enough "business pain" to make them worthwhile to fix. This paper discusses ways to understand and fix data quality using "Data profiling".
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