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Ten Habits for Data Quality: Focus on Preventing Errors at the Source
October 2010
Thomas C. Redman

Perhaps no subject is more important, or bedeviling, to those who labor to leverage their data warehouses than data quality. When populated with high-quality, trusted data, warehouses including the associated decision support, business intelligence (BI) and data mining tools are powerful enablers. They can help businesses see customers and markets in new ways, create new products and services, and improve operations. In so doing, these organizations distance themselves from competitors.

Decision-makers are smart. They instinctively know that their decisions are no better than the data on which they are based. And when they suspect the data isn't good, they don't trust the data warehouse for the really important decisions, anyway. So all of the potential to develop more complete views of customers, uncover new niches, and better manage risk lies fallow.

Fortunately, over the last 20 years leading-edge companies have learned how to systematically manage and improve data quality. Now, the 10 habits of enterprises with the best data are available to anyone.