大数据岗位有望迎来大爆炸

    大数据被亲切地称为“新石油”，并被视为能让美国日渐衰落的制造业止住下滑态势的重要砝码。尽管“数据是新石油”这个比喻并不完美，甚至不那么站得住脚（毕竟数据数量极大，还可以不断再生），但这个说法还是有它的可取之处。就像石油在上世纪初所发挥的作用一样，大数据也将推动本世纪的经济发展。只不过它可能并不会像多数人所设想的那样发挥这种作用。

    就像石油一样，企业也知道数据大量存在，而且光知道它在哪儿是远远不够的——要让这些数据产生价值，就必须提炼、加工并用合适的形式呈现出来。也和能源经济一样，数据经济也需要全身心奉献的劳动者——据一份常被引用的高德纳研究公司（Gartner Research）的分析报告称，目前仅IT领域就有440万人这样一支大军。

    不过，这两者的相似之处也就到此为止了。石油业想要找到并培训足够的劳动力开采石油从来就不用费太大的劲，但要培训娴熟的大数据专业人才就完全是另一码事了。麦肯锡公司（McKinsey & Company）的一份报告预计，到2018年仅美国在“具备深入分析能力”的大数据专业人才方面的缺口就在14万人到18万人之间——这种人才精通机器学习、统计学、及/或计算机科学，而真正实干的大数据人才就是那种知道如何将大量数据转化为有意义信息的人。

    但是，对大数据劳动力市场的这一悲观预计中常常被忽略的因素是，大数据对就业的影响远比深度分析和IT领域要更深远。企业需要的专业人才不一定是专攻深度分析专业的，但必须对大数据具有独特的悟性。这类人才并不是非要有计算机科学或统计学的学位不可。

    管理和技术咨询公司博思艾伦咨询公司（Booz Allen Hamilton）的一位副总裁最近向《信息周刊》（InformationWeek）杂志透露，他们已成功地将物理学和音乐专业的人才吸纳进了数据科学团队——这些人能创造性地思考问题。他们对计算机科学也许知之甚少，但却懂得如何运用与众不同的方法看待大数据问题。尽管众多企业或各经济体确实需要数据科学家来管理庞大的数据库，也需要信息技术团队提供相应支持，但在更大程度上，他们需要的是知识丰富、善于创造性思考的专业人才来最大限度地利用好大数据资源。

    乔治城大学（Georgetown University）麦克唐纳商学院教授贝奇•佩奇•西格曼博士是一位技术和信息系统领域的专家，他说：“随着软件、界面设计及相关领域的发展，今后分析大数据会变得更加容易。所以技术问题不会构成太大阻碍。对企业来说，更重要的是要有大量不光是会制作统计图表和分析表格，而是会利用手头信息优化决策的人才。”

    与大数据分析广泛应用密切相关的用人难题将不仅局限于企业的IT部门或专设的“数据部门”。同时也不仅仅是像数据科学家和统计学家这样的大数据专家才能从这股热潮中获益。在以数据分析为中心的领域里，如风险管理、市场营销和研究科学，与大数据有关的众多机会早已获得充分利用，不过这种应用实际上没有止境。

    IBM公司的“全球大学关系项目”（Global University Relations Programs）总监、同时也是计算机科学家的吉姆•斯伯热表示，从学术角度看，在一些本来跟数据无缘的学科里，比如社会科学和人文学科的一些分支，大数据也正在发挥重要作用。同时，在医药研究、各种产品开发和建模，以及所有研究科学中，大数据分析也正日益成为不可或缺的角色。为了保持竞争优势，企业会要求各级专业人才充分掌握大数据的有关概念，同时了解如何充分运用它们。

    Big data has been favorably cast as "the new oil" and held up as the economic counterweight to America's sinking manufacturing sector. And while the "data is the new oil" analogy isn't perfect or even necessarily sound (data is both abundant and renewable, after all), there's some merit to the metaphor. As oil did at the beginning of the last century, big data is going to drive economies in the century ahead. But it may not do so in the way that many people think it will.

    As with oil, companies know data is out there in large quantities and that it's not enough to simply know where it is -- it has to be extracted, refined, and delivered in a usable format to be valuable. And like the energy economy before it, the data economy needs dedicated people -- 4.4 million of them by 2015 in the IT field alone, according to an oft-cited Gartner Research analysis.

    But here the similarities end. The oil patch has never had much trouble finding and training enough roughnecks to get oil out of the ground, but training up skilled big data professionals is a different enterprise entirely. In the U.S. alone, a McKinsey & Company report projects a shortfall of between 140,000 and 190,000 "deep analytical" big data professionals by 2018 -- that is, people with highly technical skills in machine learning, statistics, and/or computer science, the actual hands-on big data people that know how to crunch huge data sets into meaningful information.

    But what's often overlooked in this dim projection of the big data labor market is that the impact of big data on employment goes far deeper than the deep analytics and IT fields. Companies need professionals at all levels that are not necessarily schooled in deep analytics but are nonetheless big data-savvy. These professionals don't need degrees in computer science or statistics.

    A VP at management consulting and technology advisory outfit Booz Allen Hamilton recently told InformationWeek that the company has had great success bringing physicists and music majors onto data science teams -- creative thinkers who know less about computer science and more about how to look at big data problems in a different way. Though companies and economies will certainly need data scientists to manage their massive databases and information technology teams to support them, to a far greater degree they'll need professionals knowledgeable and creative enough to leverage big data to the greatest possible advantage.

    "Advances in software, in interface design, and things like that will make it easier to analyze big data in the future," says Dr. Betsy Page Sigman, a professor at Georgetown University's McDonough School of Business and an expert on technology and information systems. "So it won't be as big of a technological hurdle. The more important thing for companies will be to have a lot of people that understand not just how to produce statistics and analytics, but understand how to make better decisions because they have this information."

    Any employment bump tied to the proliferation of big data analytics won't be confined to IT departments or even to dedicated "data divisions" that emerge within companies. And it isn't just big data specialists like data scientists and statisticians that stand to benefit from this boom. Big data opportunities are already being exploited in data-centered pursuits like risk management, marketing, and research science, but the applications are virtually limitless.

    Academically, big data is playing a role in decidedly non-data disciplines, like some portions of the social sciences and humanities, says Jim Spohrer, computer scientist and director of IBM's Global University Relations Programs. It will increasingly become integral in medical research, various kinds of product development and modeling, and all types of research science. To remain competitive, companies will require professionals at all levels that fundamentally grasp big data concepts and and know how to use them to their advantage.