Big Data Analytics
The first steps toward achieving a lasting competitive edge with Big Data analytics.
Governing Big Data isn't that different than governing other data, says David Corrigan, director of strategy for IBM's InfoSphere portfolio, which is focused on managing trusted information. Still, as Corrigan explains to IT Business Edge's Loraine Lawson, there are issues you should consider now, while governance and Big Data are still in their early days. For more on Big Data management, check out last week's Q&A in which Corrigan explains the key elements for a Big Data platform.
Lawson: You've talked about Big Data including volume, speed (velocity) and the variety. How does that change your approach to integration?
Corrigan: It changes it in a couple of ways. The first one would be governance. The problem with Big Data is we can handle any variety of information and technically that's true. Now you're at the point of having to apply it to governance and business logic and saying, "Well, hang on a second, this isn't the Wild West," so we have to think just because the technology can do it, should we? And are we allowed to? I see a lot of organizations moving to that next level of moving to an awareness phase. "Well, hang on a second, what should we put in the Big Data environment and who's allowed to see it?"
The integration challenge would be as you take the information from various sources, then what you want to do is attach metadata through that governance process to understand where they came from. Is it a trusted source? Are there any rules around who may see that particular source?
There's all kinds of uses for Big Data, if you take some into account, for example, something as simple as extending the single view of a customer - a master data management challenge. We see a lot of organizations saying, "We want to go beyond our four walls and beyond a structured MDM environment and compliment that with Big Data. What are customers saying on Facebook? What are they saying on Twitter?"
Big Data is absolutely capable of taking my Facebook profile, my Tweets, my LinkedIn profile, you name it, and analyzing it and linking it back to my customer MDM profile and saying, "I think David Corrigan's sentiment is that he's not too happy with us," but what about privacy? Have I given consent for those types of things? And then it gets into the murky area of, "Well, do I need to give consent if I'm putting it out on a public site anyway?" You want to marry those two things together and that's part of the integration challenge.
It's not just bringing in huge volume of information and moving the data, it's wrapping some intelligence and some governance around that and the metadata so that you know what to do with it in the Big Data environment. It may be that I'm not allowed to use a particular piece of data.
So that's the type of maturity that needs to be applied through integration, [so that] metadata can flow all the way through to the Big Data solution and then it will impact what's being analyzed and governed.