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商业 - 科技

创业偶像Optensity变大数据为小情歌

JP Mangalindan 2013年07月23日

大数据越来越流行,但是并不是所有的数据都是名符其实的大数据,也不是所有的大数据都真正发挥了作用。帕梅拉•艾莉亚的初创公司Optensity就是要帮助分析师和科学家迅速剖析大数据。用她的话来说,要让大数据学会唱歌。

Optensity创始人兼CEO帕梅拉•艾莉亚

    许多坐拥海量数据的组织正面临一个问题:如何理解这些数据的真实含义。

    三年前,当时还在反恐咨询机构A-T Solutions公司担任副总裁的帕梅拉•艾莉亚就发现了这个问题,同时意识到了其中蕴含的商机。她解释说:“我们注意到,尽管越来越多的人正在制造越来越多的传感器来采集数据,尽管现在有许多系统,尽管我们想方设法地理解这些数据,但我们意识到,现有的系统并不是很敏捷,无法真正跟上这个世界的变化速度。”

    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。

    问:假设现在你正站在讲台上向评委们推介你的公司。请用一句话简短地介绍一下你的产品。

    让大数据给用户“歌唱”。

    问:早在大数据成为业界术语之前,你们就已经开始从事这方面的研究了。你是否认为已经成为口头禅的“大数据”正在像“云”概念那样遭到滥用?

    我并不认为它正在被滥用,但我认为人们很容易对它产生误解,因为一个人的“大数据”可能是另一个人的“小数据”。所以有人会说,我拥有大数据。你仔细审查后就会发现,它远不及别人的大数据问题的规模。由于这个原因,不同的解决方案是好还是坏,的确取决于数据的大小。一些人最终就是这样陷于困境的,因为他们总认为自己碰到了一个真正的大数据问题,其实某种其他工具可能更加有效,但没有人愿意听别人说他们的数据其实并没有那么大。大数据并不是那么性感,对吧?(笑)所以说这是一个问题。

    问:你认为Optensity公司还会在哪些领域发挥作用?

    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)

    译者: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.

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