最值得关注的大数据公司盘点

    “图形大有可为”

    有些不太出名的公司也获得了极高的评价。

    比如KDnuggets.com董事长兼编辑格里高里•皮亚塔特斯基•夏皮罗认为，Tamr公司是“数据管理领域一家令人兴奋的创业公司，因此它获得了我的一票。”

    高德纳公司分析师斯库拉还推荐了一家叫Neo Technology的公司，这家公司推出了一个名叫Neo4j的开源图形数据库。斯库拉说：“我认为图形有很好的前途，因为图形表现出了数据之间的关系，而不是传统的微观视角。图形技术是很多企业发展最滞后的领域，但他们的解决方案可以让数据真正提供一些全新的见解。”（斯库拉还推荐了Pivotal、The Hive和Concurrent三家公司。）

    分析师科特•莫纳什推荐了Data Stax、WibiData、Aerospike和ClearStory等公司，而数据科学家皮特•斯科莫洛奇则推荐了Automatic、Planet Labs、Sight Machine、DataPad、Interana、Wise.io、LendUp、Declara、Sentinel Labs、FlipTop、Sift Science、 Import.io和Segment.io等公司。

    Paxata和Informatica两家公司出现在Ovum公司分析师托尔•拜尔的推荐榜单里，乔治梅森大学教授、数据科学家科克•博尔内则推荐了IBM、Syntasa、Actian和Tableau四家公司。

    拜尔说：“有不少从事安全性和机器学习的大数据公司正在崛起。现在缺失的是从事大数据的管理、管控和生命周期管理的创业公司。现在IBM差不多是唯一在做这方面工作的企业，不过我期待在这方面会有更多的创业公司展开行动。”

    “这些公司中的大多数最终都会消失”

    如果你已经读到了本文的此处，那么你已经看到我们的专家团队推荐的42个公司的名字了。它们首先都是科技公司，而且其中大多数是专门从事大数据技术的公司。

    但是也有些专家表示，最有意思的大数据公司根本就不是大数据公司。比如达文波特就指出，有些搞传统产品和服务的知名企业也在依靠自家积累的大数据开发自己的大数据产品。比如农业巨头孟山都公司（Monsanto），专门为中小企业提供办公室和财务管理的财捷集团（Intuit）和载重汽车公司施耐德（Schneider）等。

    达文波特说：“我认为，与其要改变你对信息的整个思考方式，改变信息与企业业务的关联方式，倒不如建立一家创业公司方便得多。大数据的一个令人兴奋的特点，就是你可以用它建立新的产品和服务。”

    他思考了一下然后补充说：“大数据仍然处于发展的初期阶段，我们还不知道企业通过这些技术赚钱有多容易。”

    不过专家们普遍认为，大数据公司的数量最终将有所稀释。

    Smarter Remarketer公司的阿波特认为：“这些公司中的大多数最终都会消失，因为大数据运动最重要的部分，是如何运用数据进行操作——也就是为企业的业务做决策，而不是光看谁能更快地处理数据。”（财富中文网）

    译者：朴成奎

    ‘Graphs have a great future’

    Some of the less well-known companies received the highest praise.

    Tamr, for instance, is “an exciting startup in data curation, so that would be my nomination,” said Gregory Piatetsky-Shapiro, president and editor ofKDnuggets.com.

    Neo Technology, the company behind open source graph database Neo4j, is another that Gartner’s Sicular pointed out. “I think graphs have a great future since they show data in its connections rather than a traditional atomic view,” she said. “Graph technologies are mostly unexplored by the enterprises but they are the solution that can deliver truly new insights from data.” (She also named Pivotal, The Hive andConcurrent.)

    DataStax, WibiData, Aerospike, Ayasdi and ClearStorywere all part of analyst Curt Monash‘s “obvious inclusion” list, he said, while Automatic, Planet Labs,Sight Machine, DataPad, Interana, Wise.io, LendUp,Declara, Sentinel Labs, FlipTop, Sift Science, Import.ioand Segment.io were among those named by data scientist Pete Skomoroch.

    Paxata and Informatica were both cited by Ovumanalyst Tony Baer; IBM IBM 0.74% , Syntasa,Actian and Tableau were four named by George Mason University professor and data scientist Kirk Borne.

    “There are a number of startups in security and machine learning that are emerging,” Baer said. “What’s missing right now are startups that look at data governance, stewardship, lifecycle management for big data. Right now IBM is largely alone, but I’m expecting there will be more startup action to come.”

    ‘Most of these companies will go away’

    If you’ve reached this point in the article, you will have read 42 recommendations by our panel of experts. All of them are foremost technology companies; most exist specifically to perpetuate big data technology.

    But some experts said that the most interesting big data companies aren’t big data companies at all. Established companies with traditional products and services are starting to develop offerings based on big data, Davenport said. Those include agriculture giant Monsanto MOO , back-office operations stalwart Intuit INTU 0.10% , and the trucking company Schneider.

    “To me, it’s much easier to create a startup than it is to change your entire way of thinking about information and how it relates to your business operation,” Davenport said. “One of the really exciting things about big data is when you use it to create new products and services.”

    He added with hesitation: “It’s early days still, and we don’t know how easy it will be for companies to make money off these things.”

    It is inevitable that there will eventually be a thinning of the big data herd, experts said.

    “Most of these companies will go away because the most important part of the big data movement will be how to use data operationally—to make decisions for the business,” Smarter Remarketer’s Abbott said, “rather than who can merely crunch more data faster.”