幾年前，人們還在竭力消化大數(shù)據(jù)的概念，如今這個概念不再火熱了。大數(shù)據(jù)已經(jīng)融入主流科技領(lǐng)域，可以被視為傳統(tǒng)數(shù)據(jù)分析的外延。

以上觀點(diǎn)來自四大國際會計事務(wù)所之一——德勤最新發(fā)布的數(shù)據(jù)分析趨勢報告。

協(xié)助撰寫報告的德勤獨(dú)立高級顧問、美國巴布森學(xué)院教授湯姆?達(dá)文波特稱：“大數(shù)據(jù)和傳統(tǒng)數(shù)據(jù)分析正在融合，越來越難以將兩者區(qū)分開來?！?/p>

“大數(shù)據(jù)”一詞通常指分析海量信息，從而幫助企業(yè)更好地做決策，以及提升公司內(nèi)部計算機(jī)系統(tǒng)性能。另外，海量信息未必要存在一處，比如甲骨文公司的數(shù)據(jù)庫，可以分布在多個數(shù)據(jù)庫和系統(tǒng)之中。

就在幾年前，企業(yè)高管還在努力理解大數(shù)據(jù)的定義，也很難找到掌握這類巨量數(shù)據(jù)分析技術(shù)的專才。

而今，高等學(xué)府已經(jīng)提供高級數(shù)據(jù)分析專業(yè)的碩士學(xué)位，企業(yè)正在開發(fā)自有項(xiàng)目，培訓(xùn)數(shù)據(jù)科學(xué)方面的人才。德勤報告舉例說，思科公司就內(nèi)部推出了數(shù)據(jù)科學(xué)的培訓(xùn)項(xiàng)目，200多員工已結(jié)業(yè)。

由于媒體報道、顧問服務(wù)，還有分析師都在大談特談“大數(shù)據(jù)”?，F(xiàn)在人們已經(jīng)大致明白大數(shù)據(jù)的概念，也了解企業(yè)可以怎樣運(yùn)用這種技術(shù)。

德勤報告提到，2010年，“大數(shù)據(jù)”還是谷歌搜索引擎的熱搜詞，此后熱度持續(xù)下滑。該報告解釋說，這是因?yàn)槟壳按蟊娨呀?jīng)了解這一概念，不再需要查詢大數(shù)據(jù)是什么意思了。

“坦白說，我覺得人們了解大數(shù)據(jù)的意愿并不十分強(qiáng)烈，更愿意實(shí)際運(yùn)用。”達(dá)文波特如是說。

時下最新的熱詞是認(rèn)知計算（Cognitive Computing），一般指模擬人類思考邏輯的計算機(jī)系統(tǒng)，運(yùn)用的是機(jī)器學(xué)習(xí)算法等人工智能技術(shù)。認(rèn)知計算系統(tǒng)可以識別語音、分辨圖像中的物體，甚至能在無人駕駛汽車中學(xué)習(xí)適應(yīng)危險的路況環(huán)境。

假如企業(yè)能利用先進(jìn)的數(shù)據(jù)分析技術(shù)解決傳統(tǒng)的商業(yè)問題，比如用IBM 旗下人工智能程序Watson提高農(nóng)場用水效率，認(rèn)知計算最終也可能得到普及，成為傳統(tǒng)數(shù)據(jù)分析范疇的技術(shù)。（財富中文網(wǎng)）

譯者：Pessy

校對：夏林

Big data is no longer the hot buzzword it was a few years ago that people strained their brains to understand. It’s now entered the mainstream and can be viewed as an extension of traditional data crunching.

That’s one of the takeaways from a Deloitte report on trends in data analytics released on Wednesday.

“Big data and traditional analytics are merging,” said Tom Davenport, an independent senior advisor to Deloitte who helped write the report and who is also a Babson College professor. “It’s getting harder and harder to distinguish the two.”

The term “big data” generally refers to the idea of analyzing enormous volumes of information to make better business decisions and improve the performance of a company’s internal computer systems. Additionally, all that information doesn’t have to be stored in one place, like an Oracledatabase, for example. It can be scattered across multiple databases and systems.

It was just a few years ago that executives struggled to understand the term and had trouble finding employees who specialized in the types of technology used to crunch tons of information.

Now, however, universities offer specialized master’sdegrees for advanced data analytics and companies are creating their own in-house programs to train talent in data science. The Deloitte report cites networking giant Ciscoas an example of a company that created an internal data science training program that over 200 employees have gone through.

Because of media reports, consulting services, and analysts talking up “big data,” people now generally understand what big data means and how they can apply it to their own business.

The Deloitte report explains that Google searches for the term “big data” in 2010 were high, but they have since declined. Davenport explained that’s because people now grasp the term and no longer need to look up what it means.

“Frankly, I think there’s less of a desire to read about this stuff, and more of a desire to do it,” said Davenport.

Now, the new hot topic is cognitive computing, which generally refers to computer systems built to simulate human thinking and reasoning using artificial intelligence techniques like machine-learning algorithms. Cognitive computing systems can recognize speech, identify objects in pictures, and even learn to adapt to dangerous road conditions if embedded within a self-driving car, for example.

If companies are able to use these advanced data crunching techniques to solve traditional business problems, such as using IBM Watson to improve water use on farms, cognitive computing might eventually be lumped in with how people view traditional data analytics.