Big data in the real world isn't so easy

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Big data is a big challenge that requires high-quality data, new approaches to data management, and more processing power. But the payoff could be a strong competitive advantage

General Motors' OnStar service, which provides drivers with remote vehicle diagnostics and responds to emergencies, already manages as much as 3 petabytes of data annually. OnStar CIO Jeffrey Liedel knows there is so much more that can be done to exploit that data for the benefit of drivers and GM's business.

For example, GM is pilot-testing a mobile app for its Chevrolet Volt electric car that would help drivers monitor their vehicle batteries and remotely manage charging them.

Competitors, including Nissan and Ford, offer similar capabilities to monitor electric vehicles, or they plan to. Drivers want manufacturers to alleviate their "range anxiety," or worry about whether an electric vehicle is about to run out of juice. But that's not all. "There's something about the electric vehicle -- you want to be connected to it," Liedel says. "The customer is more interested in analytics: How well am I driving, driving patterns, what's my fuel economy." (The Volt can also run on gasoline.)

Electric vehicle owners aren't the only ones who want deeper insight from OnStar data. Internal business users and external partners want it, too. It falls to IT, Liedel says, to deliver the data in a way that is reliable, secure, and flexible. "The key has been to recognize the importance of data and analytics," he says. "Even though sometimes it's not core to running a transactional system, it's a key part of running the business."

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