Do You Need Big Data Governance? Maybe.

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Sunil Soares is a widely known figure and authority in the field of data governance, the author of two books on the topic and the former director of IBM’s Information Governance consulting practice. He’s been a contributor to Information Management and recently spun himself off as founder and managing partner at Information Asset LLC., where he continues to help organizations build data governance practices. His third book, “Big Data Governance, an Emerging Imperative,” is the first comprehensive volume on the new data phenomenon from a governance perspective. He recently spoke about the purpose and timing of this work with Information Management Editorial Director Jim Ericson. 

Information Management: Your new book subtitles big data governance as “emergent.” How emergent is it in reality?

Sunil Soares: Candidly, when I talk to CIO and CTO clients about big data governance, they say, “great, but I am focused on governance of small data.” So it’s early but approaching quickly. When you delve a little bit into what they are doing you find they are all dealing with big data even if they don’t think of it that way. I spoke to an insurance company looking at telematics data where the policyholder agrees to place a sensor on the car that monitors their driving.

I’ve seen the Progressive Insurance ads and their Snapshot device that works like that.

Many insurance companies, not just Progressive, are experimenting with that kind of device now. But my point of this example is, it raises tremendous governance implications. There are privacy questions because now the insurance guy knows where the car has been. There is also a potential issue around data quality. When you research some of these sensors you find they can produce defective or duplicate readings that have to be weeded out. And then there is the information management lifecycle perspective, which is how long do I need to keep the sensor data?

Data governance authority and author Sunil Soares.

That’s a good example of sensor data governance, what about something more human?

Okay, take the example of a retailer that wants to integrate social media data with master data. I spoke to a retailer in the process of doing that and told him it sounded like a great idea, right? He clued me into some implications though, like the fact that Facebook, for example, has very specific platform policies around what it can and cannot do with data listed right at its site. For example, if I’ve got your name in my master data management system and you decide to ‘like’ my company on Facebook and have a phone number there, I can’t just take your phone number to my master. Facebook’s written policy platform policy says if you decide to “unfriend” my business I have to delete all of your data. If I’m holding a golden record with that information, I am in trouble. So there are very specific big data governance issues, I call them emergent, not far along but not always a very thoughtful process either.

I would expect most of this experimenting is quarantined from things like master records anyway. Are your clients still mostly experimenting?

Yes, that is the case. And as governance goes, it’s really about the data, not the technology of big data. In my book I created a three-axis chart. The x-axis accounts for the big data types like social, machine, sensor, biometric or big transaction. The y-axis is all the different industries and the z-axis really looks at the governance implications. When you put that in front of organizations and say, “Given these big data types, are you doing some or all of them today?” The answer is they probably are. They didn’t necessarily think of that as big data but they suddenly see they need governance.

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