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  • Okay. So you've probably heard of big data.

    好的,你大概聽過大數據。

  • But you may be wondering what is it?

    但你可能還是好奇它究竟是什麼?

  • And why should I care?

    為什麼要關注它?

  • For starters, big data is, well, big.

    首先,大數據真的很「大」。

  • Data has been getting bigger for a while now.

    資料量不斷變得越來越大。

  • From the dawn of time to less than a decade ago, mankind generated about 5 exabytes of data.

    從人類出現開始到十年前,人類已經產生了約有5EB的資料量。

  • In 2012, global data will grow to 2.7 zettabytes.

    2012年,全球資料量將會成長到2.7ZB。

  • That's five hundred times more data than all data ever generated prior to 2003.

    這也是2003年前所產生的資料量的500倍。

  • And it's gonna grow three times bigger than that by 2015.

    而到了2015年,資料量將成長三倍。

  • One of the big reasons the data is getting bigger

    資料量不斷變大的重要原因之一

  • is that it's continuously being generated from more sources and more devices

    在於越來越多資料源與裝置正不斷產生新的資料。

  • and much of that data like videos, photos, comments, and social media forums, reviews on websites, and so on is unstructured.

    而許多資料像影片、照片、留言、社交媒體討論串以及網站上的評論等等都是非結構化資料。

  • That means the data isn't stored within structured predefined tables.

    非結構化資料指的是非儲存於結構化預定格式上的資料。

  • Instead, it's often made of volumes of text, dates, numbers,

    相反的,它通常由大量的文本、日期、數字所構成。

  • and facts that are typically free form by nature.

    而這些基本上都是自由格式。

  • Certain data sources are arriving so fast that not even time to store it before applying analytics to it.

    某些資料來得太快,以至於在分析它們之前來不及儲存。

  • And that's why traditional data management and analytics tools alone don't enable IT to store, manage, process, and analyze big data.

    而這就是為什麼傳統資料管理和分析工具無法使IT部門儲存、管理、處理與分析大數據。

  • So, we could just ignore big data?

    所以我們可以因此忽略大數據?

  • After all, is it worth the effort?

    畢竟,它值得嗎?

  • Turns out, it is.

    結果是值得的。

  • A recent Gartner study concluded only ten to fifteen percent of organizations will take full advantage of big data.

    Gartner最近做的一項研究發現,只有百分之十到十五的組織有志於充分運用大數據。

  • But those they do will out-perform their unprepared competitors by 20 percent across major financial metrics.

    但這些組織的主要財務表現將比其他沒有準備的競爭對手高出百分之二十。

  • And that's, you guessed it, big.

    你猜對了,這相當了不起。

  • But in order to generate that level-up insight and competitive advantage from big data,

    但為了從大數據中得到相當程度的洞察力與競爭優勢,

  • innovative new approaches and technologies are required

    組織必須具備創新方法與科技

  • because the big data you're looking at is like a mountain

    因為大數據就像一座山,

  • and you're trying to uncover those tiny.

    而你所試圖開發的只是一小部分。

  • But game changing, competitors' macking, golden nugget of insight and knowledge

    但遊戲規則的改變、競爭者的攻擊與寶貴的洞見與知識

  • that transform how effectively you do business.

    都會改變你業務的效率。

  • Imagine a logistics company mining data on truck pickup and delivery schedules and real time traffic patterns.

    想像有一間物流公司正收集卡車裝箱、運送排程以及即時交通概況的資料。

  • The data they're using combines real time GPS beat from trucks, public traffic pattern data,

    他們所使用的資料結合了卡車GPS的即時回饋、公共交通資料

  • RFID data from cargo that has been picked up or dropped off and other sources.

    無線射頻辨識系統以及其他資訊。

  • Now, imagine they get a call for a new pickup.

    現在,他們接到了一通新的訂單。

  • Which truck should they send?

    他們該指派哪一台卡車?

  • The closest one, right?

    最近的那台,沒錯吧?

  • What if the route for the closest truck has a heavy traffic jam?

    但如果最近的那輛卡車遇到嚴重的塞車呢?

  • Or what if the cargo loaded on that truck doesn't allow space for the new pickup?

    又如果那輛卡車沒有多餘的載貨空間呢?

  • Or maybe the route for that truck involves a series of steep grade changes?

    又或者那輛卡車的行駛路線有一系列的陡坡變化?

  • In those cases, the closest choice may not be the best choice

    在這種情況下,最近的卡車可能不是最好的選擇。

  • It might be more costly, less efficient, or unable to even service the customer's needs.

    它可能花費更多、更沒效率,甚至無法滿足顧客需求。

  • But the only way to arrive at the optimal decision is to analyze multiple big data sources in real time.

    分析多樣即時資料是找出最佳決策的唯一辦法。

  • And that's just one quick example of how big data can make a big impact on the company's bottom line.

    而這只是一個簡單的例子,說明大數據如何深深影響公司的盈虧。

  • You can find out more about Big Data what it is, how to use it, and data center strategies for taking advantage of it by visiting us on the web.

    藉由造訪我們的網站,你可以更深入了解大數據為何以及如何使用它的資料中心策略。

Okay. So you've probably heard of big data.

好的,你大概聽過大數據。

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大數據如何發揮極大影響力(Intel Big Data 101: How Big Data Makes Big Impacts)

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    Anastasia Hsu 發佈於 2014 年 07 月 20 日
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