Too many big data initiatives start with nebulous goals. Executives from MetLife and Tivo Research Analytics pipe up on getting practical.
One of the best pieces of advice I've heard on making use of big data is to avoid boil-the-ocean experiments and stick with the problems you know.
That advice, offered by Infochimps CEO Jim Kaskade, resonated as I organized "Big Data Innovation: Time To Focus," a panel discussion slated for the upcoming CIO Summit, Oct. 2, part of the Interop conference in New York.
I had in mind Kaskade's advice to "prioritize business use cases first and start solving problems one at a time" when I selected panelist Gary Hoberman, senior VP and CIO of regional application development at MetLife. The insurer had been staring down the problem of developing a 360-degree view of customers for some 10 years before finally tackling the problem with the help of NoSQL technology -- specifically MongoDB.
Where customer service reps and claims researchers previously had to open as many as 15 screens accessing 70 disparate systems in order to resolve customer questions and settle claims, their window into this information is now the MongoDB-based MetLife Wall, which was inspired by Facebook's timeline view of individuals.
So what's Hoberman's advice for making use of big data? He's actually fairly new to MetLife, having joined from Citibank a little over a year ago, and he says the key to solving an old problem was instilling a sense of "intrepreneurship" among the development team.
"You have to think like a startup and act like a startup and just get it done," says Hoberman. "The questions about what methodology you use aren't as important as just believing that you can get it done."
In a big company you have to track development work and have rigorous processes in place to ensure compliance, Hoberman says, but he stresses the importance of giving people latitude to be innovative and to enjoy and believe in what they are doing. That won't happen in a stifling, "this is how we do things" atmosphere.
A bit of the advice from panelist Mark Lieberman, CEO at Tivo Research Analytics (TRA) is to plan a crawl-walk-run path to automation. Automated action based on real-time insight is where things are headed in digital media.
"Real-time is the Shangri-La where a bunch of data goes in and ads get placed automatically, programmatically in real time," Lieberman explains. "Three to five years from now in television, [manual methods] go away; it all happens in technology using big data."
TRA is a big supplier of TV viewing data mashed up with everything from consumer packaged goods purchases and car-buying data to privacy-compliant insight into credit card usage and use of prescription drugs. "Push-button buying" is already a reality in online advertising, and it's moving to television. More than likely the same sorts of automated approaches will move to other industries, so start dreaming up that roadmap today -- it can't happen all at once.
This is just a small sampling of the advice I expect to hear at our CIO Summit, so if you're in the New York area on Oct. 2, please join us. If you can't make it, stay tuned for follow-up coverage from the event. I'm certain there will be a boatload of practical advice for making the most of big data.
Gary Hoberman and Mark Lieberman will be two of the speakers at Interop's CIO Summit Oct. 2. The Interop New York Conference and Expo, Sept. 30-Oct. 4, 2013, provides the knowledge and insight to help IT and corporate decision-makers bridge the divide between technology and business value. Through three days of educational conference sessions, two days of workshops, real-world demonstrations on the Expo Floor and live technology implementations in its unique InteropNet program, Interop New York provides the forum for the most powerful innovations and solutions the industry has to offer.
6 Tools to Protect Big DataMost IT teams have their conventional databases covered in terms of security and business continuity. But as we enter the era of big data, Hadoop, and NoSQL, protection schemes need to evolve. In fact, big data could drive the next big security strategy shift.
Big Data Brings Big Security ProblemsWhy should big data be more difficult to secure? In a word, variety. But the business won’t wait to use it to predict customer behavior, find correlations across disparate data sources, predict fraud or financial risk, and more.
Join us for a roundup of the top stories on InformationWeek.com for the week of April 24, 2016. We'll be talking with the InformationWeek.com editors and correspondents who brought you the top stories of the week!