UPDATED 15:30 EST / NOVEMBER 20 2018

BIG DATA

Data governance does more than thwart GDPR police — a lot more

Dread of data misuse has spread through all kinds of organizations since the General Data Protection Regulation went live in May. The legislation hasn’t done much to lighten the already drab image of data governance in people’s minds. To get all departments on-board governance missions, companies might lay down the sticks and try a carrot for a change.

“Governance is just a horrible word,” said Chris Bannocks (pictured, left), group chief data officer at ING Bank N.V. “People have really negative connotations associated with it.”

It begins with metadata, or the data about an organization’s data. It isn’t a word that generally excites business people — they may not even know what it means. When they found out it involves applying thousands of labels to tons of data, they might not want to hear anymore. This is where leaders in the organization must explain how much there is to gain from properly governed data, according to Bannocks.

Bannocks and Steven Eliuk (pictured, right), vice president of deep learning, Global Chief Data Office, at IBM, spoke with Rebecca Knight (@knightrm) and Paul Gillin (@pgillin), co-hosts of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, during the IBM CDO Summit in Boston, Massachusetts. They discussed tools and tricks that can lighten a company’s data-governance load. (* Disclosure below.)

‘Do it or else’ is maybe not the best data-governance project name

Data governance isn’t as scary as it sounds. It just means knowing what and where data is, who’s responsible for fixing it if something goes wrong, and being able to measure whether it’s right or wrong in the first place, according to Bannocks.

What many are justifiably scared of, though, is the sheer volume of data that needs to be governed in a large organization. This is where machine-learning tools — like IBM’s automatic metadata generation technology — can help.

Machine learning can help pick out outliers and exceptions so people don’t have to comb through all data, outliers, and exceptions. “You can’t do this across 30,000 elements in any meaningful way or way that really makes sense from a financial perspective [without ML],” Bannocks said.

When people’s jobs get easier through well-governed data, they start to appreciate it more, according to Eliuk. “We’ve seen process times go from 90 days down to a couple days. That’s a huge reduction,” he said.

Aside from reduction in process time, all-around better analytics and business decisions come out of governance.

“We’re talking about quality, and quality means better decisions, and that’s actually all governance is,” Bannocks concluded.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the IBM CDO Summit. (* Disclosure: TheCUBE is a paid media partner for the IBM CDO Summit. Neither IBM, the event sponsor, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

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