First of a two-part report
What do Facebook, Groupon and biotech firm Human Genome Sciences have in common? They all rely on massive amounts of data to design their products. Terabytes and even zettabytes of information about consumers or about genetic sequences can be harnessed and crunched.
The practice is called big data, and as the term suggests, it is huge in both scope and power. Analyzing big data enables anything from predicting prices to catching criminals, and has the potential to impact many industries.
One way to understand how big data works is to think about your daily life. You write an email, call your boss, pass a security camera, maybe buy a plane ticket online. Taken alone, this is disjointed, boring information. To Elizabeth Charnock, it makes up your digital character.
“Digital character is this idea that almost everybody these days leaves behind a giant digital breadcrumb trail,” she says.
Charnock founded Cataphora, a company that can process huge amounts of this sort of data about employees to determine patterns. She says those patterns can predict everything from a person’s mood to their skill as a manager to a person’s inclination to commit fraud.
Take rogue trader Jerome Kerviel, who cost his French bank billions of dollars in losses.
“His cell phone bill was literally an order of magnitude larger than any of his coworkers — why?” Charnock asks. “Well, because he wanted to put less things in writing. He almost never took vacation, even though French people love to take vacation.”
Charnock says Kerviel also circumvented usual trading and communication protocols.
“Any one of those things, you kind of say, ‘So what?’ But what we look for is a number of them that on the surface perhaps don’t seem to be related but all seem to be happening at the same time,” she says.
Charnock says had the French bank analyzed that data, it might have flagged the rogue trader earlier.
But big data is not just about connecting dots to detect crime. The ability to process so much information and process it so quickly makes all kinds of things possible that weren’t before. So LinkedIn finds jobs or people you might like to know about, and biotech companies can analyze gene sequences in billions of combinations to design drugs.
Data analytics itself is not new. Two decades ago, Wall Street hired teams of physicists to analyze investments. But in the last couple of years, computing, storage and bandwidth capacity have become so cheap that it has altered the scale of what’s possible.
Now, with very little money, a gifted student or a small startup can design big-data applications.
“Everywhere you look, there’s an opportunity to collect more data and then apply a statistical or mathematical approach to understanding what’s happening,” says Chris Kemp, chief executive officer of Nebula, a firm that provides storage and computing capacity for other companies to be able to process their big data applications.
Kemp says ultimately big data will give consumers better tools so they can do a better job of predicting things like prices, such as whether an airfare is likely to go up or down. Farmers can do a better job of insuring their crops if they can forecast the weather with greater accuracy.
Oren Etzioni, a professor of computer science at the University of Washington, says this trend is fueling intense demand for mathematics and computing talent.
“We have seen the industrial revolution, and we are witnessing a data revolution,” Etzioni says.
He’s started three big-data companies. One of them, Decide.com, employs four Ph.D.s to design better programs to forecast prices on consumer electronics.
Etzioni says a good data scientist can write algorithms that filter data, understand what it’s telling you, and then graphically represent it. The end result is like getting a bird’s-eye view of a vast territory of information.
Big data can, and occasionally does, go wrong. Comic examples of that include mismatched recommendations, like “My TiVo thinks I’m gay.” “But think about a company divulging your Web surfing history with your name attached and you begin to get a sense of how big data opens the door to new possibilities of security or privacy breaches.
James Slavet, a venture capitalist at Greylock Partners, says his firm invests in companies that use big data creatively and responsibly. He says data does not stand in for human judgment.
“They do use it to make the judgment more sound, more objective and to hopefully lead to better decision making,” he says.
Slavet calls big data a tectonic shift, one that will continue to affect many things we do for decades to come.