Data are an enterprise asset, and data governance (DG) is about establishing policies, processes, rules, standards, and controls around data to improve the quality of data and ensure data security and privacy.¹

However, organizations struggle to implement data governance and, as a result, face a large number of challenges. These challenges either prevent the DG program from gaining ground in the first place or derail the program at some point after takeoff.

According to data-governance expert John R. Talburt, “The first adopters usually had to make two, or even three, attempts before seeing any success. However, like any new paradigm, it takes time to iron out the wrinkles.”

Data governance and the car brakes

One of the challenges around data governance, and one of the key reasons behind data governance resistance and failure in organizations, is that data governance is viewed as unnecessarily restrictive. But that doesn’t have to be the case. Varun Pant, director of IT for Swati Consultancy and formerly national president for DAMA Australia, says, “Data governance is like a brake in a car. It is not there to slow you down, but enables you to go faster, more safely.”²

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