Big Data

You Too Can Be Nate Silver


You Too Can Be Nate Silver

Photograph by Archive Photos/Getty Images

Well, it would seem we have identified the week in which being a big data wonk became cool. After all, there’s Nate Silver—the Electoral College Oracle—being feted on The Daily Show and across the Web for collecting polling data and then massaging it with a clever algorithm. Now everyone wants to hang out with the skinny, kinda nervous dude who knows his way around R. (R? Look it up. You’ll need this for cocktail parties from here on out.)

If you don’t have time to attend the soon-to-be-planned Nate Silver’s Datapalooza, you can still have a crack at becoming the big data star around the office. That’s because the data fiends in Silicon Valley have been hard at work creating software that lets mere mortals run complex information analysis jobs. Some of the best examples of this type of technology can be seen at the Alteryx Analytics Gallery, where you can find ready-made apps for poring over data ranging from census figures to how a merger between two companies may play out.

Alteryx’s main business revolves around selling software that helps people submit big data sets and then choose from a menu of analytical operations to perform on the information. The idea is to remove some of the coding grunt work that has surrounded data analysis jobs for decades. “This has been the world of statisticians and Ph.D.s and not the people on the front lines trying to make good business decisions,” says George Mathew, the president and chief operating officer at Alteryx. “We wanted to change that.”

Customers using Alteryx’s software will find some huge, preloaded data sets like information from the 2010 Census and marketing services company Experian’s consumer profiling data. Then you can literally drag and drop analysis functions such as regression models from a menu to apply them to the data and receive a pretty report at the end. Companies can, of course, supply their own data, making it possible for, say, an executive at a retailer to take data from 900 million point of sale transactions, 2.5 million loyalty cards, and 500,000 Likes on Facebook (FB) and try to determine what the value of Facebook Likes might be on a given store.

The Analytics Gallery is a spot where people can find prepackaged data analytics apps and have some fun poking around on the information. Ahead of the presidential election, for example, there were models available that let you see how particular zip codes might vote based on polling numbers and things like census data. The Presidential Election App predicted Obama’s win with Silver-like accuracy.

One of the newer apps has been tuned for Facebook employees trying to cash in on the company’s initial public offering. It helps you find the ideal house based on how many Facebook shares you’re willing to sell, how close you want to live to the company headquarters, and the usual bedrooms and bathrooms desired.

Alteryx’s Mathew hopes these types of apps will prove that more people can become data analysis whizzes if they’re given the right tools. He says there are 200,000 so-called data scientists in the world, who regularly command more than $200,000 per year in salary. These are your Nate Silvers. Then, there are 2.5 million people in the workforce that have enough statistics, business, and math knowledge to do some serious data crunching with a bit of technological help. “I think there’s a tremendous arbitrage opportunity here,” Mathew says.

Hear that, Silver?

Vance_190
Vance is a technology writer for Bloomberg Businessweek in Palo Alto, Calif. Follow him on Twitter @valleyhack.

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