????他們說：大數(shù)據(jù)將拯救世界，改變我們做生意的方式，還會(huì)告訴我們很多不了解的事。

????這些說法中有些可能會(huì)成為現(xiàn)實(shí)，有些可能不會(huì)——但關(guān)鍵在于，圍繞“大數(shù)據(jù)”所開展的大肆造勢(shì)鋪天蓋地，亟需做點(diǎn)剖析。這項(xiàng)技術(shù)確實(shí)有前景，但濫用這個(gè)說法就是另一碼事了。

????不管實(shí)際情況如何，“大數(shù)據(jù)”仍然是個(gè)新興領(lǐng)域。對(duì)各行各業(yè)來說，要從自己的數(shù)據(jù)中心及美國(guó)政府的數(shù)據(jù)庫(kù)新開放的數(shù)據(jù)寶藏中發(fā)掘各種商業(yè)機(jī)會(huì)還為時(shí)尚早。伯克利大學(xué)（Berkeley College）教授達(dá)爾尚?德賽稱，看看“谷歌趨勢(shì)”（Google Trends）就會(huì)發(fā)現(xiàn)——“大數(shù)據(jù)”直到2011年還很少被用作搜索詞，直到2012年才真正開始流行。

????不過德賽說：“我還是新技術(shù)的超級(jí)擁躉，我深信有很多技術(shù)可以用來改善生活?！?/p>

????德賽是在一個(gè)研討會(huì)上發(fā)表這些觀點(diǎn)的。這個(gè)研討會(huì)名為“理解大數(shù)據(jù)”，主要由學(xué)者參加，是由紐約大學(xué)城市科學(xué)與進(jìn)步中心（Center for Urban Science and Progress）的康斯坦丁?康托可斯塔組織的，與會(huì)者還有來自普拉特學(xué)院（the Pratt Institute）、圣弗朗西斯學(xué)院（St. Francis College）和紐約技術(shù)學(xué)院（the NYC College of Technology）的專家。它是“科技三角U”（Tech Triangle U）的一個(gè)組成部分，后者是由布魯克林科技三角（Brooklyn Tech Triangle，紐約新興科技創(chuàng)新中心——譯注）發(fā)起的一個(gè)項(xiàng)目，旨在推動(dòng)布魯克林科技界和學(xué)術(shù)圈建立聯(lián)系。

????每位與會(huì)專家都就大數(shù)據(jù)未來將對(duì)自己的研究領(lǐng)域產(chǎn)生什么樣的影響闡述了自己的看法。康托可斯塔領(lǐng)導(dǎo)著一支開展建筑信息學(xué)研究的團(tuán)隊(duì)，主要研究如何用數(shù)據(jù)科學(xué)來分析城市能源消費(fèi)。他在會(huì)上預(yù)先透露了對(duì)《第84本地法》（Local Law 84）推行后一些公開數(shù)據(jù)的研究成果。這個(gè)法案要求紐約市大型建筑必須披露對(duì)能源和水的利用情況，但它只要求公布相關(guān)數(shù)據(jù)——并沒有要求這些建筑改變能源運(yùn)用方式。不過他表示，它確實(shí)為這些建筑做出改變帶來了兩種壓力。

????第一種就是競(jìng)爭(zhēng)壓力，因?yàn)檫@些建筑將密切關(guān)注同類建筑的情況，同時(shí)開始根據(jù)能源利用效率爭(zhēng)取住戶?？低锌伤顾f：“我們能利用這一點(diǎn)比較紐約不同地區(qū)的能源利用情況，還能了解住戶能源消費(fèi)水平的差異。”

????它意味著像Radiator Labs這類公司將有望打開市場(chǎng)。這家公司的產(chǎn)品基于無線局域網(wǎng)工作，能解決老舊建筑中蒸汽供暖水平不均的問題。隨著基準(zhǔn)數(shù)據(jù)開始讓物業(yè)經(jīng)理明白他們和同類建筑在能源利用水平上存在差距，他們可能就會(huì)對(duì)這種產(chǎn)品產(chǎn)生興趣。

????康托可斯塔稱，第二種壓力將來自上層。紐約公用事業(yè)公司Consolidated Edison已開始設(shè)法通過新的方式來管理峰值需求，也就是在用能高峰期間向大客戶付錢，讓他們自愿減少能耗。有了更多能源使用數(shù)據(jù)后，能源基準(zhǔn)數(shù)據(jù)城市的大型公用事業(yè)公司可能就能開發(fā)出更好的節(jié)能戰(zhàn)略。它包括和EnergyHub這樣的公司合作，招募消費(fèi)者參加自愿項(xiàng)目，在能耗趨于峰值時(shí)通過設(shè)備和互聯(lián)網(wǎng)將家里的空調(diào)調(diào)整幾度，或者干脆斷電。

????圣弗朗西斯學(xué)院的埃米莉?霍洛維茨表示，光收集一大堆數(shù)據(jù)還遠(yuǎn)遠(yuǎn)不夠。要想更好地改變現(xiàn)狀，搜集數(shù)據(jù)只是必需的一步，但還很不充分。她說：“在我看來，大數(shù)據(jù)最大的問題在于，通過它能看到太多東西。”憑借大數(shù)據(jù)技術(shù)，研究者終于能首次把眾多不同數(shù)據(jù)放在一起，但這并不意味著他們就能揭示什么新東西。這樣確實(shí)能揭示相關(guān)性——但要證明因果關(guān)系就要難得多。

????與會(huì)專家還有普拉特學(xué)院的杰西?布雷登和紐約市立大學(xué)的杰森?蒙哥馬利，但大數(shù)據(jù)什么時(shí)候，以及怎樣才能催生大家能感受到的與眾不同的客戶服務(wù)，他們并沒有解決這個(gè)問題。眾多新技術(shù)公司都宣稱更多數(shù)據(jù)將帶來更好的服務(wù)——個(gè)性化電子商務(wù)就是其中一個(gè)領(lǐng)域，也就是說，如果你在某個(gè)電商平臺(tái)上評(píng)論了更多產(chǎn)品，這個(gè)網(wǎng)站就會(huì)產(chǎn)生更好的產(chǎn)品改進(jìn)建議——但現(xiàn)在還不清楚這種說法到底有多大的真實(shí)性。

????不過，各類提供數(shù)據(jù)服務(wù)的公司正在大張旗鼓地展示，它們正在幫助各類企業(yè)積聚、利用它們業(yè)已收集到的數(shù)據(jù)。同時(shí)各種數(shù)據(jù)代理商也正在收集數(shù)量驚人的關(guān)于消費(fèi)者身份及（大致）需求的各類信息。

????不過與會(huì)專家都認(rèn)同的一點(diǎn)是，細(xì)節(jié)決定成敗，獲得這么多數(shù)據(jù)是一回事，要真正理解它們、用好它們卻完全是另一碼事。大數(shù)據(jù)可能會(huì)越來越流行，但要真正獲得重大成功仍然需要努力。（財(cái)富中文網(wǎng)）

????譯者：清遠(yuǎn)

????Big data will save the world, they say. It will change the way we do business, they say. It could tell us things we didn't know we didn't know, they say.

????Some of that might be true and some of it may not -- but the point is that the hype around the term "big data" is thick enough to require a chainsaw to cut through. The technology is promising; the semantics are another story.

????Whatever the reality, "big data" remains a nascent field. Businesses are a long way from seeing all the opportunities that could come of the newly opened troves of data in their data centers and in those of the U.S. government. Just look at Google Trends, Berkeley College professor Darshan Desai said -- "big data" was barely used as a search term until about 2011 and didn't quite take off in popularity until 2012.

????Still, "I'm a big fan of the new technology," Desai said. "I believe there are ways to make lives better."

????Desai made her remarks as part of a panel of academics led by Constantine Kontokosta of the NYU Center for Urban Science and Progress. The panel, called "Making Sense of Big Data" also featured scholars from the Pratt Institute, St. Francis College, and the NYC College of Technology. It was part of Tech Triangle U, an initiative by the Brooklyn Tech Triangle to connect the technology and academic communities in Brooklyn.

????Each scholar demonstrated how they thought big data would impact their fields of study. Kontokosta, who leads a building informatics research group that focuses on the application of data science to the analysis of urban energy consumption, gave a preview of some of his work on data released under Local Law 84, an energy and water usage disclosure law for large buildings in New York City. The law itself is pure data -- nothing in it forces buildings to change their practices around energy. But it does create two kinds of pressure on buildings to change, he said.

????The first is competitive pressure, as buildings monitor their peers and begin to compete for residents on efficiency. "We can use this to compare how much energy use is varying across the city," Kontokosta said, "but also how much the difference is in how much people are paying."

????Which means companies like Radiator Labs, which offers a Wi-Fi-enabled product that addresses uneven steam heating in old buildings, may start to see property managers taking interest in their wares as benchmark data starts to show that they aren't keeping up with peer structures.

????The second pressure will be from the top, Kontokosta said. The New York utility company Consolidated Edison is already working to manage peak demand by paying large customers to voluntarily reduce energy consumption during peak demand. With more usage data, big utilities in energy benchmarking cities may be able to develop better demand reduction strategies. Those could involve partnerships with companies like EnergyHub to recruit customers into voluntary programs where home thermostats can be adjusted, by the utility and over the Internet, a few degrees when demand is spiking and a blackout is possible.

????But assembling a bunch of data isn't enough, said Emily Horowitz of St. Francis College. It's necessary but not sufficient to make change for the better. "The big problem with big data, in my view, is you can see all kinds of things," she said. Researchers may be able to put many different kinds of data side by side for the first time thanks to big data technology, but that doesn't mean that they have revealed anything. Correlations, sure -- but proving causation is much more difficult.

????The panelists, which also included Pratt's Jessie Braden and CUNY's Jason Montgomery, did not address the questions of when and how big data will deliver appreciable differences in consumer services. Many new technology companies have claimed that more data leads to better results -- e-commerce personalization is one such area; if you rate more products on a retailer's website, you are told that it will lead to better product suggestions on that site -- but it's unclear how true that statement actually is.

????Nonetheless, companies offering data services are making a strong showing helping businesses aggregate and make use of the data they're already collecting. And data brokers are collecting an alarming array of information about who we are and what we (presumably) want.

????But the devil is in the details, and making sense of all that information is an entirely different proposition from merely accessing it, the panelists agreed. Big data may be increasingly popular, but it's still looking for its first big hit.