Data Governance Primer

By Jill Dyché Print this article Print

Guidelines for defining data governance and formalizing it as a sustainable set of practices.

Standard industry intelligence says that corporate data volumes double every 18 months, but mobile and online data are growing at an even faster clip. From corporate cost containment, regulatory compliance, strategic “voice of the customer” initiatives and beyond, the need for businesses to manage proliferating data has never been more urgent.

Enter data governance. The term has become as buzz-worthy with businesspeople as it is with their IT colleagues. Nevertheless, both sides continue to struggle with how to define data governance and how to formalize it as a sustainable set of practices.

The term “governance” has bounced from the political world to corporate boardrooms, landing squarely in the laps of IT executives, who have been busy formalizing their IT governance initiatives. Despite the term entering the lexicon, there is still some confusion about what data governance actually means, what work is involved with it and who should own it.

IT organizations have begun to recognize the need to define terminology and business rules around data that is increasingly shared across business processes and organizations. As part of efforts to rein in costs, CIOs are starting to understand the enormous and often-replicated efforts involved in finding, gathering, annotating, consolidating and deploying data to support a growing project portfolio.

Unaware that this work has already been performed for other projects, well-meaning developers roll up their sleeves and integrate the data yet again. The expense of this duplication is buried, but it can cost a large company millions of dollars in excess labor hours.

Increasingly, data governance is coming to the attention of businesspeople, many of whom have begun to develop workarounds due to the lack of available data that’s meaningful, integrated and easily accessible. It’s a phenomenon that’s become rampant across industries, resulting in enormous costs.

“I’ve developed my own database to protect myself from other people’s databases,” one health care provider says wryly. “I can’t trust other people’s interpretation of data about my patients. If I have to stay late and maintain my own Access database, that’s what I have to do.”

Multiply this clinician’s efforts by the number of clinicians in the hospital network, and you’ll get an idea of the costs—and the risks—involved.

This article was originally published on 2011-07-28
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