A recent report by the Data Warehousing Institute claims that the annual cost of poor data quality for U.S. industries is $611 billion. This includes direct costs of analyzing and correcting data errors and indirect costs as well.For instance, when errors become exposed to customers and regulators, fines can follow and the backlash can force an avalanche of expensive changes to how an insurance company conducts its business.

These costs can undermine the breakthrough insight that a data warehouse has long promised: managers using customer data to develop targeted new products and gain market share; actuaries using data to more accurately price risk and evaluate loss reserves; and agents using data to grow and maintain customer relationships.

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