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Errors in data can cost a company millions of dollars, alienate customers, and make implementing new strategies difficult or impossible. The author describes a process AT&T uses to recognize poor data and improve their quality. He proposes a three-step method for identifying data-quality problems, treating data as an asset, and applying quality systems to the processes that create data.
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