Are you governing your data governance?

Enterprises that are ambitious about leveraging big data tend to focus most of their attention on three big questions: 1) What are our goals with data analytics? 2) What analytics tools do we use? 3) Where do we get the analytics talent?

Critical questions, to be sure. Yet there’s another big data consideration that, if left unresolved, can subvert the integrity of your data analytics operation: How do we effectively govern our data?

Big data is about more than sheer volume: It’s also about the scope of data available for the first time ever, as well as the growing number of sources providing both structured and unstructured data — personal mobile devices, mobile apps, geo-location technology, social media, and the Internet of Things, just to name the obvious ones.

Collecting and storing big data is a great start to the actual process. But as Forbes contributor Margaret Harrist writes, “many organizations have become far more focused on collecting and storing data than they have been at deciding who can access it, how they can use it, and under what circumstances.”

This can lead to problems with security, government regulations regarding data privacy, and data integrity. That last one is especially dangerous because it could result in business decisions based on unknowingly faulty data.

Effective data governance is rooted in establishing policies and creating controls surrounding data access. Specifically, enterprises must determine which employees or partners can create, access, modify, copy or remove data, and then implement appropriate levels of access.

Data governance might not be as sexy as, say, predictive analytics, but without it enterprises run a number of unnecessary risks.

Is your enterprise staying on top of its data governance responsibilities?

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