FORTUNE — Big data will save the world, they say. It will change the way we do business, they say. It could tell us things we didn’t know we didn’t know, they say.

Some of that might be true and some of it may not — but the point is that the hype around the term “big data” is thick enough to require a chainsaw to cut through. The technology is promising; the semantics are another story.

Whatever the reality, “big data” remains a nascent field. Businesses are a long way from seeing all the opportunities that could come of the newly opened troves of data in their data centers and in those of the U.S. government. Just look at Google Trends, Berkeley College professor Darshan Desai said — “big data” was barely used as a search term until about 2011 and didn’t quite take off in popularity until 2012.

Still, “I’m a big fan of the new technology,” Desai said. “I believe there are ways to make lives better.”

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Desai made her remarks as part of a panel of academics led by Constantine Kontokosta of the NYU Center for Urban Science and Progress. The panel, called “Making Sense of Big Data” also featured scholars from the Pratt Institute, St. Francis College, and the NYC College of Technology. It was part of Tech Triangle U, an initiative by the Brooklyn Tech Triangle to connect the technology and academic communities in Brooklyn.

Each scholar demonstrated how they thought big data would impact their fields of study. Kontokosta, who leads a building informatics research group that focuses on the application of data science to the analysis of urban energy consumption, gave a preview of some of his work on data released under Local Law 84, an energy and water usage disclosure law for large buildings in New York City. The law itself is pure data — nothing in it forces buildings to change their practices around energy. But it does create two kinds of pressure on buildings to change, he said.

The first is competitive pressure, as buildings monitor their peers and begin to compete for residents on efficiency. “We can use this to compare how much energy use is varying across the city,” Kontokosta said, “but also how much the difference is in how much people are paying.”

Which means companies like Radiator Labs, which offers a Wi-Fi-enabled product that addresses uneven steam heating in old buildings, may start to see property managers taking interest in their wares as benchmark data starts to show that they aren’t keeping up with peer structures.

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The second pressure will be from the top, Kontokosta said. The New York utility company Consolidated Edison is already working to manage peak demand by paying large customers to voluntarily reduce energy consumption during peak demand. With more usage data, big utilities in energy benchmarking cities may be able to develop better demand reduction strategies. Those could involve partnerships with companies like EnergyHub to recruit customers into voluntary programs where home thermostats can be adjusted, by the utility and over the Internet, a few degrees when demand is spiking and a blackout is possible.

But assembling a bunch of data isn’t enough, said Emily Horowitz of St. Francis College. It’s necessary but not sufficient to make change for the better. “The big problem with big data, in my view, is you can see all kinds of things,” she said. Researchers may be able to put many different kinds of data side by side for the first time thanks to big data technology, but that doesn’t mean that they have revealed anything. Correlations, sure — but proving causation is much more difficult.

The panelists, which also included Pratt’s Jessie Braden and CUNY’s Jason Montgomery, did not address the questions of when and how big data will deliver appreciable differences in consumer services. Many new technology companies have claimed that more data leads to better results — e-commerce personalization is one such area; if you rate more products on a retailer’s website, you are told that it will lead to better product suggestions on that site — but it’s unclear how true that statement actually is.

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Nonetheless, companies offering data services are making a strong showing helping businesses aggregate and make use of the data they’re already collecting. And data brokers are collecting an alarming array of information about who we are and what we (presumably) want.

But the devil is in the details, and making sense of all that information is an entirely different proposition from merely accessing it, the panelists agreed. Big data may be increasingly popular, but it’s still looking for its first big hit.