????我感覺許多行業都在熱情擁抱大數據——比如制造業和金融服務業，因為人們已經有了熟練操作計算機的能力。但是我覺得人們急著想要看到的是，大數據應用在他們的生活中會給他們帶來哪些好處。他們對大數據還是比較關心的，而且他們確實只想享受大數據給他們帶來的好處。這需要做大量的工作。而現在的數據學家還是太少了，像Hadoop這樣的公司更是鳳毛麟角，你還得需要一個計算機科學專業的研究生來把這些東西建立起來。大數據已經從根本上改變了數據儲存的單位比特成本，這是一個結構性的變化。

????現在圍繞大數據已經能清晰地看到一個“啞鈴”態勢的形成。服務業和信息密集型產業等具有大量知識型員工的行業明顯會從大數據中獲得巨大的效益。還有零售業、酒店業、股票交易……如果你有發現趨勢的能力，你就能發現你所在業務的分界點，然后采取相應措施。如果你發現了如何利用市場中的某些事件隨勢而動，那么你肯定可以把它轉化成現金。這就是啞鈴的其中一端。

????啞鈴的另一端是工業互聯網。我覺得它特別特別的有趣。通用電氣公司（GE）有一篇文章寫道，你不僅要能賣飛機引擎，還要賣飛機引擎的周邊價值。所以要圍繞大數據激發一些行動。比如對于通用電氣來說，就是對已經賣出去的引擎做預防性的維護。這個理念對通用電氣、西門子（Siemens）以及其它任何一家制造企業都具有重大意義。你可能認為大數據只是知識方面的一項業務，但是在工業方面，它也是一個非常有意思的“啞鈴”。

????但對于其他行業來說……你能預測時尚行業的趨勢和流行的顏色嗎？什么元素可以讓一季時裝獲得成功？或許大數據能做到。另外一部好電影就是一部好電影，大數據本身造就不了一部好電影。有時你只能一步一個腳印地創造一些東西。一本好書，一部電影，只有到了上架上映的時候才知道好不好。“啞鈴”理論看起來非常站得住腳。

????那么我們是否應該告訴有些企業：“大數據不適合你”？

????我們應該搞清楚這個問題。因為如果我們不搞清楚，大家會很不高興。你不能讓一個問題半死不活地吊著，而是要徹底搞定一個問題。很多人只想立刻上馬搞大數據，但是如果你不想投資到一個有效的水平——那需要一筆重大的投資——而只是蜻蜓點水地投一點錢，就指望收獲巨額回報，這種好事是不會發生的。所以如果你今年沒有足夠的預算，那么或許你應該等等，因為這種技術會越來越便宜。所以不妨寬心安坐，最好用軟件即服務（SaaS）和云應用給你的公司打氣，讓你的市場部門放手拼搏。

????從根本上看，企業的高管就是投資者。高管是做什么的？就像我們的投資人之一本?霍洛維茨說的那樣，他們做的不是事，而是決策。沒什么比一個半生不熟的大數據項目更悲劇了。這樣做只會讓你對大數據的真正效益產生反感和不信任。

????大數據市場還有哪些可以進入的空白領域？哪些領域或行業是大數據可以輕易征服、但目前仍然是完全敞開的？

????所有這些變化正在把所謂的負空間（即相連事物之間的空間）變成戰場。如果這些領域不互相交流的話，單是你自己花多少錢沒有意義。但由于發生了巨大的變化，所以我們看到了很多的負空間。比如人們正在關掉傳統的數據存儲倉庫，還有我們發現很多企業應用轉移到了云端。Salesforce是這樣做的，Workday做的也很好，另外還有API、物聯網、數據……大數據還處于發展的早期階段，但它很可能將成為有史以來最好的信息來源。你能有多少條形碼？大家肯定會在工業方面看到大數據的賺錢能力。

????把負空間結合在一起是個大問題。但它們目前仍然是一片空白。我們還有很長的路要走。（財富中文網）

????譯者：樸成奎

????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.