????大家可能早就聽說過Facebook公司的工程師訓練營。這是一個為期六周的上崗培訓項目，主要是讓新員工深入學習公司的代碼庫，同時了解公司文化。過去幾個月里，這個社交網絡巨頭還悄悄地推出了另外一個項目，它不是專門面向工程師的——而是要教所有員工學會使用大數據工具。

????Facebook的數據分析部門主管肯?魯丁說：“我們的確希望每個人都覺得自己有能力運用數據。這樣一來，數據分析師（又稱數據達人）就不會成為完成任務的瓶頸了。分析師是專門待命去執行特種部隊式的任務的，就是那些不管規模，還是深度都非一般人所能企及的任務。”

????Facebook旗下約有100名這類分析師（并且分析師隊伍還有大量職位正虛位以待）。不過，曾任社交游戲公司Zynga分析師與平臺技術副總的魯丁表示，他想在公司推廣這樣一種文化，使每個人都能用數據測試、并最終推出新產品、設計修改和其他改進。為此，魯丁和他的團隊已經嘗試推出了各種教授如何運用數據分析工具的輔導課程。去年11月，他們推出了首個為期兩周的大數據課程，現在正在持續不斷地授課。而后續還將推出各種課程。每次為期兩周的課程最多能容納25名員工——包括產品經理，客服人員，公司基礎架構團隊成員。他們在這兩周里每天都要上課，上午是三小時集中授課，下午完成自選項目。每個學員這兩周中都會有一位專職導師輔導，公司希望他們每個人都能解決一個公司面臨的實際問題（比如如何運用數據提供更好的客戶服務）。

????Facebook本來就一直靠數據進行決策，同時依靠真實用戶來測試新產品。它開發了自己的大數據工具，幫助所有員工——而不僅僅是分析師——方便快速地在其它龐大的數據庫中進行查詢。比如，HiPal就是一個旨在讓公司所有員工都能方便地分析高達拍字節數據的工具。Gatekeeper是另一個工具，管理Facebook每天開展的成百上千個用戶測試項目，它能確保這些測試提供“從統計角度而言有意義的結果。”

????不過魯丁強調，開展這種培訓絕不僅僅是為了推廣合適的工具——它的根本目的還在于培養員工的思維能力。公司的大數據訓練營負責教員工如何進行探索性分析并得出假設，還訓練他們有效溝通并演示自己的分析成果。魯丁說：“我認為，如果我們堅持現在的做法，最后就能達成目標，那樣就能培養一種特有的公司文化，每個人都會感到數據是他們開展工作必須運用的一部分。每個人都應該具有數據分析的能力。”

????當然，魯丁和他的團隊自己也正在運用數據弄清楚如何改進下一屆訓練營——哪些課程最有效，如何才能確定課程的最佳規模。要找到天賦出眾的分析師本身就夠困難的了（更別說高昂的費用），而要讓Facebook近5,000名員工自愿參加數據分析培訓也不那么容易。其他公司會效法嗎？對Facebook的公司文化來說，這種兩周的強化課程很有意義，因為這種訓練營式的項目早就是新晉工程師的必經儀式。不過，訓練員工學會運用大數據工具——同時培養數據分析的意識，對其他公司來說也頗有裨益。（財富中文網）

????譯者：清遠

????You may have heard of Facebook's engineering bootcamp, a six-week onboarding program for new hires to learn the ins and outs of the company's code base and culture. But over the last few months, the social networking giant has quietly rolled out another program that's not just for engineers -- rather, it's focused on teaching big data tools to all employees.

????"We really want everyone to feel like they are capable of using data," says Ken Rudin, head of analytics at Facebook (FB). "Then analysts [a.k.a. data crunchers] aren't a bottleneck to getting things done. They're there for doing the SWAT team type of things, things that take a little extra scale and more depth than your average person would have."

????Facebook employs about 100 so-called analysts (and lists plenty of open positions for its analytics team). But Rudin, formerly VP of analytics and platform technologies at Zynga (ZNGA), says he wants to promote a culture in which everyone uses data to test and ultimately roll out new products, design changes, and other improvements. To that end, Rudin and his team have experimented with different kinds of tutorial sessions on using data analytics tools. Last November, they launched the first two-week session on big data and are now running courses back to back; there is a wait-list for upcoming sessions. Each two-week course consists of up to 25 employees -- product managers, customer service workers, and members of the company's infrastructure team, for example. They come in every day for two weeks, sitting in on about three hours of lectures each morning and then taking the rest of the day to work on self-selected projects. Each employee is assigned a mentor for the duration of the two weeks and is expected to work on a real company problem (such as how to use data to provide better customer service).

????Facebook has a history of data-driven decisions and running tests on real users to try out new products. The company has developed homegrown big data tools to help all sorts of employees -- not just analysts -- quickly and easily run queries on its immense data sets. HiPal, for example, is a tool that aims to make analyzing petabytes of data easy for anyone in the company. Gatekeeper is another tool that manages the hundreds of user tests Facebook runs each day and makes sure that they provide "statistically meaningful results."

????But Rudin stresses that it's not just about having the right tools -- it's about the right mindset. The company's big data bootcamp teaches employees how to conduct exploratory analysis and come up with hypotheses. It also trains them to effectively communicate and present their findings. "If we continue down the path that we're going, and I think we'll get there, then we'll have a culture where everyone feels that data is something they should be using as part of their job," says Rudin. "Everybody should be doing analysis."

????Of course, Rudin and his team are also using data to figure out how to evolve their new bootcamp -- what type of curriculum is most effective and how they can best scale the courses. While finding talented analysts is hard (not to mention expensive), putting Facebook's nearly 5,000 employees through a voluntary boot camp on crunching numbers isn't easy either. So will other companies follow suit? A two-week intensive course makes sense for Facebook's culture, where a bootcamp-style program has become a rite of passage for incoming engineers. But other companies could benefit from training employees to adopt a big data toolset -- and mindset.