????許多坐擁海量數據的組織正面臨一個問題：如何理解這些數據的真實含義。

????三年前，當時還在反恐咨詢機構A-T Solutions公司擔任副總裁的帕梅拉?艾莉亞就發現了這個問題，同時意識到了其中蘊含的商機。她解釋說：“我們注意到，盡管越來越多的人正在制造越來越多的傳感器來采集數據，盡管現在有許多系統，盡管我們想方設法地理解這些數據，但我們意識到，現有的系統并不是很敏捷，無法真正跟上這個世界的變化速度。”

????于是，她攜手 IT工程師斯科特?齊默一起創建了Optensity公司。他們的目標是：打造一個系統，以協助分析師和數據科學家迅速決策，而且無需擔憂數據的位置、格式化方式和演變方式。Optensity公司推出的第一款產品AppSymphony主要被應用于情報監視和偵察社區（Intelligence Surveillance and Reconnaissance，簡稱ISR），目前已有三家客戶正在用它剖析監測數據。

????本周，50歲的艾莉亞將在財富頭腦風暴技術會議（Brainstorm Tech Conference，7月22日至24日在科羅拉多州阿斯彭研究所召開）上，與4位其他選手共同角逐本年度創業偶像大賽（Startup Idol）的桂冠。我們提前問了她幾個簡單的問題。

????問：假設現在你正站在講臺上向評委們推介你的公司。請用一句話簡短地介紹一下你的產品。

????讓大數據給用戶“歌唱”。

????問：早在大數據成為業界術語之前，你們就已經開始從事這方面的研究了。你是否認為已經成為口頭禪的“大數據”正在像“云”概念那樣遭到濫用？

????我并不認為它正在被濫用，但我認為人們很容易對它產生誤解，因為一個人的“大數據”可能是另一個人的“小數據”。所以有人會說，我擁有大數據。你仔細審查后就會發現，它遠不及別人的大數據問題的規模。由于這個原因，不同的解決方案是好還是壞，的確取決于數據的大小。一些人最終就是這樣陷于困境的，因為他們總認為自己碰到了一個真正的大數據問題，其實某種其他工具可能更加有效，但沒有人愿意聽別人說他們的數據其實并沒有那么大。大數據并不是那么性感，對吧？（笑）所以說這是一個問題。

????問：你認為Optensity公司還會在哪些領域發揮作用？

????一個突然涌現的事物就是所謂的“物聯網”（Internet of Things）。我認為，我們的工具未來有可能在這個領域發揮作用。因為物聯網基本上是一個由傳感器構成的世界，當數據開始擺脫傳感器，發現有趣的事情時，人們可以在傳感器上計算。嘿，房間里好長時間沒人了，但空調還在轉。就是這類事情。所以我們需要在那里安置兩個傳感器：一個物理傳感器，顯示沒有人在走動。另一個傳感器說空調正在運轉。所以我們認為，這類問題是數據在未來可以大顯身手的領域。（財富中文網）

????譯者：任文科

????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.