Automate where possible

Although organisations cannot rely on technology to solve their data governance problems, there are a number of tasks that can be greatly aided with the appropriate tools. Master data management and data quality software are two examples of established technologies that can help.

Of course, a certain degree of automation is required simply to process data in volume. “You can’t hope to begin to cope with the larger volumes of data that are being generated without some form of automation,” argues DQM Group’s Gregory. “And databases will grow very quickly even in more modest-sized and smaller businesses.”

That said, some explicit data governance tasks such as implementing data policies across the organisations, are currently underserved by technology perhaps because the best practice has yet to be established. “There haven’t been formal ways of doing it,” says Bloor’s Howard.

This is likely to change, however, as more organisations pursue data governance and the opportunities for automation are better understood.

Measure success

Peter Done

Peter Done is managing director of Peninsula Business Services, the personnel and employment law consultancy he set up having already built a successful betting shop business.

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