Big data applications: Real-world strategies for managing big data
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LAS VEGAS -- Organizations launching a "big data" management and analytics project should focus their initial efforts...
on "customer-centric outcomes," according to Martin Wildberger, vice president of worldwide information management at IBM.
Wildberger -- who spoke before a crowded room yesterday at the IBM Information on Demand conference -- said the goal of focusing on customer-centric outcomes is all about understanding how to use big data to deal more effectively with clients.
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Sprint shares its big data story
Sprint is one example of an IBM customer that can relate to the goal of using big data to improve customer service.
One of the largest telecommunications companies in America, Sprint has nearly 54 million customers and offers a host of products for consumers, businesses and government. The company recently began using IBM InfoSphere Streams and analytics tools to try to make sense of the mountains of data created by Sprint network users on a daily basis.
"As a carrier, we have a lot of transactions going on per day," said Von McConnell, Sprint's executive director of advanced analytics labs, who joined Wildberger on stage. "In fact, I would surprise you with the number but it is multiple, multiple billions of transactions per day."
One of the goals of the initiative, McConnell said, is to use all that information to gain new insights about how customers use Sprint's network and, ultimately, figure out ways to improve and personalize the customer experience. He said his company still has a long way to go on that front, but is making progress.
"Until recently we hadn't even considered trying to harness that data," McConnell said. "But what's happening now at Sprint is that we're trying to understand: What is this data? How can we use it? What does it mean?" He said his team is now asking questions of the data in an effort to predict network activities and prevent negative customer experiences.
"I truly believe it's going to revolutionize telecommunications in general because it's moving us from optimization of data to more asking questions of data," McConnell said. "It's not easy, but the net of it is we're going to get there. There is so much value in just using data. We're just glimpsing the future of this."
IBM offers more big data tips
Wildberger -- who was quoting recommendations stemming from a 2012 IBM Institute of Business Value survey -- had several other pieces of advice for organizations launching a big data management strategy.
In addition to focusing on customers when they get started, Wildberger said, organizations should also take some time to create an enterprise-wide big data blueprint. The blueprint should detail how each part of the organization plans to take advantage of the big data initiative. "Make sure that as you approach this new frontier that you [look at] how your organization is going to leverage all of this new insight," he said.
It's also a good idea to start with existing data -- information that is already stored in-house -- and to focus initially on short-term goals. "You don't need to start at the complicated end of the spectrum. Start with the data that you have to achieve short-term results," Wildberger said. "Build off of that, and then go and get buy-in [from your] organization on the power of this capability."
The next step is to start building or acquiring the skills necessary to carry out the initiative. That could mean recruiting new talent or training existing team members on big data technologies. It's important to keep skill sets in line with the organization's business priorities, Wildberger said.
Finally, Wildberger said, make sure that the use cases for big data management and analytics are based on easily measurable business outcomes. "That's pretty sound logic in terms of where to go as you approach this big data story," he said.
Mark Brunelli is the news director for SearchDataManagement.com. Follow him on Twitter: @Brunola88.