During the big data land grab of 2014, everybody seemed to have become a data scientist, practically overnight. Despite the circus-like atmosphere, Hilary Mason and her new applied data analytics firm, Fast Forward Lab, rose above the din.
Mason did cool stuff at her Brooklyn-based firm, like use a shiny new Hadoop cluster to measure media signals to calculate, once and for all, the answers to important societal questions, like which people like better: cats or dogs.
“This was a massive waste of energy,” Mason said during her keynote address at AnacondaCON earlier this year. “And the idea that we had computational power so cheap that we could apply it to something so absolutely trivial really blew my mind.”
It wasn’t all fun and games at Fast Forward Labs, of course. The firm, whose tagline was “reporting on the recently possible,” had real clients paying real money to get real answers. But it’s the data science tools that Fast Forward Labs shared with the public – such as Pictograph, which uses deep learning to analyze photos on Instagram, and Probabilistic Real Estate, which predicts real estate prices in New York City – that showed us what was possible with data.
Mason, who cut her teeth as the chief scientist at bit.ly before striking out on her own (she’s still the Data Scientist in Residence at Accel Partners), seemed to epitomize the modern data scientist: comfortable with new compute platforms like Hadoop, new processing approaches like deep learning, and new data types like social media.
“I make beautiful things with data,” Mason wrote on her personal blog. “I believe technology should give us superpowers. At Fast Forward Labs, we are building those superpowers.”
So when Cloudera announced last week that it was acquiring Fast Forward Labs, it seemed to indicate that something has changed.
As the biggest distributor of Apache Hadoop and related technologies, Cloudera is certainly no stranger to data science. But as a publicly traded company trying to claim market share in a super-competitive emerging market, Cloudera is at a different stage as a company than Fast Forward Labs.
Achieving results, not building beautiful products, is Cloudera’s primary focus now that its stock is traded on the New York Stock Exchange under the symbol CLDR. It wants more quarters like the last one, where CLDR exceeded analyst expectations in revenue and profit. With $260 million in revenue last year and more than 1,000 employees, Cloudera is also a much bigger company than Fast Forward Labs.
Despite the differences in size and goals, Cloudera intends to lean on Mason and company to help drive its machine learning story. As Cloudera’s new vice president of research, Mason will be asked “to give Cloudera a much clearer view of the future of the field,” according to Cloudera co-founder Mike Olson.
“This merger adds outstanding talent to Cloudera’s already-deep bench,” Olson wrote in a blog post last week. “Anyone who’s ever met Hilary knows she is amazing — a gifted scientist, a compelling speaker, an able operator. I could not be more pleased to have her here. She and her co-founder, Micha Gorelick, bring us a very strong research and development team.”
While Cloudera isn’t strictly in the algorithms business like Fast Forward Labs was, the acquisition makes sense to Mason because Cloudera is a company “that drives progress in the foundational technologies our work relies on,” Mason wrote on the Fast Forward Labs blog.
The potential to leverage Cloudera’s considerable scale to deliver new data products to even more customers seemed to be at the top of Mason’s list of reasons to accept Cloudera CEO Tom Reilly’s offer.
“We built a profitable company with real impact on our clients’ products and businesses. I’m proud of what we’ve accomplished,” Mason wrote. “However, we’re just getting started. The enterprise is more excited about machine learning and applied artificial intelligence than ever, and in order to meet this growing opportunity, we are heading in a new direction.”
Mason says the change in logo won’t impact Fast Forward Labs’ existing research and advisory services clients. Let’s hope it doesn’t impact Mason’s creative flair for using emerging tech to show us what beautiful things we can create with data.