于是，她携手 IT工程师斯科特•齐默一起创建了Optensity公司。他们的目标是：打造一个系统，以协助分析师和数据科学家迅速决策，而且无需担忧数据的位置、格式化方式和演变方式。Optensity公司推出的第一款产品AppSymphony主要被应用于情报监视和侦察社区（Intelligence Surveillance and Reconnaissance，简称ISR），目前已有三家客户正在用它剖析监测数据。
本周，50岁的艾莉亚将在财富头脑风暴技术会议（Brainstorm Tech Conference，7月22日至24日在科罗拉多州阿斯彭研究所召开）上，与4位其他选手共同角逐本年度创业偶像大赛（Startup Idol）的桂冠。我们提前问了她几个简单的问题。
一个突然涌现的事物就是所谓的“物联网”（Internet of Things）。我认为，我们的工具未来有可能在这个领域发挥作用。因为物联网基本上是一个由传感器构成的世界，当数据开始摆脱传感器，发现有趣的事情时，人们可以在传感器上计算。嘿，房间里好长时间没人了，但空调还在转。就是这类事情。所以我们需要在那里安置两个传感器：一个物理传感器，显示没有人在走动。另一个传感器说空调正在运转。所以我们认为，这类问题是数据在未来可以大显身手的领域。（财富中文网）
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.