Since my last column on data governance (DG) was published (see the June 2005 issue of DM Review), I have had several people ask me to write a column on how to develop a DG methodology. As much as I'd like to, I can't. Why? Because every business is unique, and I don't believe there should be a single, one-size-fits-all methodology for developing and implementing DG standards and policies. What I can do, however, is give you an outline of the structural elements that any comprehensive DG methodology (or strategy, or plan or whatever you wish to label it) should contain.

Any DG methodology should stress strong leadership and commitment by senior management. C-suite commitment is critical to achieve high-quality data and financial reporting mandated by the 2002 Sarbanes-Oxley Act; executives now must attest to the accuracy of those reports. However, a good DG methodology will turn those requirements into an asset by instilling a culture of data quality throughout the organization. The best way to achieve and maintain leadership and commitment to enterprise-wide data quality and governance is to form a data management governance council (DMGC) comprising data owners throughout the organization, as well as representatives from IT.

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