Scott Rudin

What I learned at Facebook's big data bootcamp

June 13, 2013: 7:18 AM ET

The social network wants all its employees to learn how to use data.

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FORTUNE -- 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).

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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.

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