Startup Idol: How Optensity makes big data seem minusculeJuly 19, 2013: 1:46 PM ET
Pamela Arya's startup helps analysts and scientists parse through big data quickly.
FORTUNE -- The problem facing many organizations sitting atop massive amounts of data is how to make any sense of it.
Three years ago, Pamela Arya, then a vice president at the counterterrorism firm A-T Solutions, recognized the problem and saw an opportunity. "We noticed that even though more and more people were building more and more sensors to capture data, the systems, and the way we make sense of that data, we realized the existing systems weren't very agile and couldn't really keep up with the rate of change in our world," she explains.
So along with IT engineer Scott Zimmer, she co-founded Optensity. Their goal: build a system to assist analysts and data scientists in making decisions quickly without worrying about where the data is located, how it's formatted, and how it's changing. Optensity's first product, AppSymphony, is largely being used within the Intelligence Surveillance and Reconnaissance, or "ISR," community by three clients to make sense of surveillance data.
Next week, Arya, 50, will vie as one of five contestants for the mantle of this year's Startup Idol competition at Fortune's Brainstorm Tech conference, at the Aspen Institute in Colorado. We caught up with her beforehand for a few quick questions.
Let's say it's next week, and you're onstage selling your company to the judges. Give us your elevator pitch in one sentence.
Making big data "sing" to its users.
You guys were working on big data before it became industry parlance. Do you think "big data" as a catch phrase is now being abused the way, say, "cloud" was?
I don't think it's being abused, but I think it's very easy to have misunderstandings because one person's "big data" is another person's "small data." So someone will say, I have big data. When you look at it, it's nowhere near the size of someone else's big data problem. Because of that, different solutions are better or worse depending really on the size of that data. That's how people can end up having problems because they think, Oh, we've got a really big data problem, when some kind of other tool would work better ... But nobody wants to hear that their data really isn't that big. Big data isn't that sexy, is it? [laughs] So that's a problem.
How else do you see Optensity becoming useful?
One thing popping up is called the "Internet of Things." That's an example where we think our tool could be really useful in the future. Because the Internet of Things is basically a world of sensors, where you would compute on the sensor as the data is throwing off the sensor to find out interesting things. Hey, nobody's been in the house for a while, but the air conditioner is still running. That kind of thing. So you needs two sensors there: a physical sensor. No one's moving around. Another sensor saying the air conditioning's running. So those kinds of problems are where we see the future of where data is going.