警惕大数据的“哑铃”现象

    我感觉许多行业都在热情拥抱大数据——比如制造业和金融服务业，因为人们已经有了熟练操作计算机的能力。但是我觉得人们急着想要看到的是，大数据应用在他们的生活中会给他们带来哪些好处。他们对大数据还是比较关心的，而且他们确实只想享受大数据给他们带来的好处。这需要做大量的工作。而现在的数据学家还是太少了，像Hadoop这样的公司更是凤毛麟角，你还得需要一个计算机科学专业的研究生来把这些东西建立起来。大数据已经从根本上改变了数据储存的单位比特成本，这是一个结构性的变化。

    现在围绕大数据已经能清晰地看到一个“哑铃”态势的形成。服务业和信息密集型产业等具有大量知识型员工的行业明显会从大数据中获得巨大的效益。还有零售业、酒店业、股票交易……如果你有发现趋势的能力，你就能发现你所在业务的分界点，然后采取相应措施。如果你发现了如何利用市场中的某些事件随势而动，那么你肯定可以把它转化成现金。这就是哑铃的其中一端。

    哑铃的另一端是工业互联网。我觉得它特别特别的有趣。通用电气公司（GE）有一篇文章写道，你不仅要能卖飞机引擎，还要卖飞机引擎的周边价值。所以要围绕大数据激发一些行动。比如对于通用电气来说，就是对已经卖出去的引擎做预防性的维护。这个理念对通用电气、西门子（Siemens）以及其它任何一家制造企业都具有重大意义。你可能认为大数据只是知识方面的一项业务，但是在工业方面，它也是一个非常有意思的“哑铃”。

    但对于其他行业来说……你能预测时尚行业的趋势和流行的颜色吗？什么元素可以让一季时装获得成功？或许大数据能做到。另外一部好电影就是一部好电影，大数据本身造就不了一部好电影。有时你只能一步一个脚印地创造一些东西。一本好书，一部电影，只有到了上架上映的时候才知道好不好。“哑铃”理论看起来非常站得住脚。

    那么我们是否应该告诉有些企业：“大数据不适合你”？

    我们应该搞清楚这个问题。因为如果我们不搞清楚，大家会很不高兴。你不能让一个问题半死不活地吊着，而是要彻底搞定一个问题。很多人只想立刻上马搞大数据，但是如果你不想投资到一个有效的水平——那需要一笔重大的投资——而只是蜻蜓点水地投一点钱，就指望收获巨额回报，这种好事是不会发生的。所以如果你今年没有足够的预算，那么或许你应该等等，因为这种技术会越来越便宜。所以不妨宽心安坐，最好用软件即服务（SaaS）和云应用给你的公司打气，让你的市场部门放手拼搏。

    从根本上看，企业的高管就是投资者。高管是做什么的？就像我们的投资人之一本•霍洛维茨说的那样，他们做的不是事，而是决策。没什么比一个半生不熟的大数据项目更悲剧了。这样做只会让你对大数据的真正效益产生反感和不信任。

    大数据市场还有哪些可以进入的空白领域？哪些领域或行业是大数据可以轻易征服、但目前仍然是完全敞开的？

    所有这些变化正在把所谓的负空间（即相连事物之间的空间）变成战场。如果这些领域不互相交流的话，单是你自己花多少钱没有意义。但由于发生了巨大的变化，所以我们看到了很多的负空间。比如人们正在关掉传统的数据存储仓库，还有我们发现很多企业应用转移到了云端。Salesforce是这样做的，Workday做的也很好，另外还有API、物联网、数据……大数据还处于发展的早期阶段，但它很可能将成为有史以来最好的信息来源。你能有多少条形码？大家肯定会在工业方面看到大数据的赚钱能力。

    把负空间结合在一起是个大问题。但它们目前仍然是一片空白。我们还有很长的路要走。（财富中文网）

    译者：朴成奎

    I feel there is an embrace of big data in many industries -- manufacturing, financial services -- because people have a fluency of computing. But I think what people are anxious for is to see the benefits of big data applied in their lives. They're somewhat concerned. They really just want to get the benefits of it. That needs work. There are too few data scientists. Hadoop is still somewhat of a unicorn -- you still need a graduate degree in computer science to set things up. It has fundamentally changed storage in terms of cost per bit. It's a tectonic shift.

    What is very clear is a "barbell" strategy around big data. Services, information-rich industries with knowledge workers in them? It's very clear there's a big benefit of big data. Retail, hospitality, trading stocks -- if you have the ability to discover trends, you can find breakpoints in your business and take care of them. If you discover how to take advantage of certain events in the market, you can certainly take that all the way to the bank. That's one end of the barbell.

    The other end of the barbell is the industrial Internet. I think that is extremely, extremely interesting. There's a really interesting writeup by GE saying that you will not just be able to sell aircraft engines but sell value around the [operation] of that engine. Trigger actions around the data. Do preventative maintenance on the engine. That concept has enormous implications for GE, Siemens, everybody who manufactures stuff. You would think that big data would only be a business on the knowledge side, but on the industrial side, there's a whole barbell that becomes very interesting.

    But other industries . . . can you predict trends and fashions and colors in the fashion industry? What makes a particular season successful? Maybe. A better movie is a better movie. Big data doesn't make a better movie. Sometimes you just have to create something. You know a well-made book or movie when you see it. The barbell strategy seems extremely sound.

    So should we be telling some companies, "Big data is not for you"?

    We should be clear. Because if we're not clear around it, people will be disgruntled. You can't wound a big data problem; you have to kill it. People want to just step in it. But if you're not willing to fund it at an effective level -- and it is a substantial investment -- to expect substantial returns by just tickling the chin, it's not going to happen. So maybe you don't have the budget this year, and maybe you should wait -- it will get cheaper. Sit tight! You're better off replenishing the guts of your company with SaaS and cloud applications and emancipate your marketing department.

    Fundamentally, the c-suite are investors. What does an executive make? As Ben Horowitz, one of our investors, says: They don't make things, they make decisions.There's nothing worse than a half-baked, half-funded big data project. That's the worst of all. You're creating a bad feeling about the true benefit of this.

    Where's the slack in the market for big data? Which areas or industries could be easily conquered but are still wide open?

    All this change is causing the negative space [between connected groups of things] to become the battleground. If things don't talk to each other, it doesn't matter how much you've spent. So we actually see a lot of negative space because there are huge changes. People are unplugging traditional data warehouses. We see a lot of business applications flying to the cloud. Salesforce did it; Workday is on a roll. And the APIs and Internet of Things and data -- it's in the early stages, but it quite likely will be the greatest source of information the world has ever seen. How many barcodes can you have? You will see the monetization of that, distinctly, on the industrial side.

    Putting it together is a large problem, and you know what? It's wide open. Boy, we have a long way to go.