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A%20New%20Data%20Analytics%20Company%20From%20A%20Boisterous%20Sta%2081c5dbbaca8e432dbaee5e2580afb856/960x0.jpg Peter Bailis, founder and CEO of Sisu Peter Bailis can’t resist dropping more than a dozen f-bombs as he explains how his startup Sisu aims to upend traditional business intelligence and reshape the way companies act on the massive amounts of information—about products, sales, customers, etc.—that they generate and store. “It’s a product problem plus a tech problem.” While an endless number of tools help companies store, sort and visualize their tsunami of data, he says Sisu goes a step further. “And no one can match our speed or the result quality.” Bailis, a former Stanford researcher and assistant professor currently on leave, founded Sisu last year, but the so-called operational analytics company is emerging from stealth Wednesday with a $52.5 million Series B round of funding led by NEA, with participation from Andreessen Horowitz and Green Bay Ventures, bringing its total funding to $66.7 million. Instead, it processes the massive amounts of data related to a given goal (increase conversion rates) and ranks which factors are currently affecting it, effectively telling companies why a metric is changing. A%20New%20Data%20Analytics%20Company%20From%20A%20Boisterous%20Sta%2081c5dbbaca8e432dbaee5e2580afb856/960x0%201.jpg Sisu customers can, for example, drill down on which factors are affecting a key performance … [+] Ben Horowitz, who led his firm’s investments in Sisu’s Series A and B, says that both Bailis’ tech chops and his approach to making machine learning usable, impressed him. “There are two ways companies are going about the market: They’re either basically building more graphs and pretty pictures, or they’re applying deep learning for predictions,” Horowitz says, “What Sisu built doesn’t look like anything else out there: It just shows you why things are happening.” Gartner analyst W. Roy Schulte says that the old approach to business intelligence, where analysts check dashboards once a day, has evolved as storing and analyzing data has become more inexpensive and companies can pump out reports in nearly real-time. The name of the company comes from a Finnish concept that roughly translates to tenacity and determination, which Bailis says captures the both the technological hurdle of sorting through massive amounts of data as well as the platform’s objectives.