Information quality (IQ) and data quality (DQ) are becoming the new buzzwords. Many organizations have IQ or DQ projects under way in some shape or form, whether in the context of data warehousing, CRM or e-business. Software providers are quickly developing new data quality products. Consultants are jumping to hang IQ or DQ on their list of services.

However, I must raise a warning flag! There are many attempts to apply the words "data quality" or "information quality" to practices that are, in fact, not quality management. There are practices that simply automate and institutionalize information scrap and rework. There are practices of quality "assessment" that fail to provide a true measure of data accuracy. There are practices that in the name "data quality" actually create new data quality problems –­ by design! There are some who propose a "maturity model" for data quality that is only a taxonomy –­ it does not correlate to a true Quality Maturity Model as described by Philip Crosby.

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