The company scored a $28 million Series B investment led by Battery Ventures with help from FirstMark, Serena Capital and Alven. Today’s money brings the total raised to almost $45 million. Its most recent priot round was a $14 million Series A in October 2016.
Dataiku has developed Dataiku Data Science Studio (DSS), which CEO Florian Douetteau says has been designed to solve communications problems between data analysts and data scientists.
“It’s a platform for working together. Data analysts can click around the data while applying machine learning, and data scientists can code and do whatever they want to do to extend the work of analysts,” Douetteau told TechCrunch.
“Data science is no longer a niche subsector of analytics like it was 20 years ago,” Neeraj Agrawal, general partner at investor Battery Ventures said in a statement. “The DSS product enables technical data scientists to work alongside data analysts to help build and deploy models into production. We feel that a platform that allows users of different skill sets to work together is the future of data science products,” he added.
Douetteau says the platform is more than just an extension of business intelligence tools we’ve been seeing since the 1990s. His company is enabling the analysts to work on the data in much more sophisticated ways, while collaborating with more technical people in the same interface. As an example, he says that one of the big use cases is media buying.
Say for example that your company wanted to buy ads in Northern Ireland. You could use DSS to find ad data to determine the best time of day to run your ads. You could then find the perfect medium for your ad buy, whether that’s radio, TV, print, online or some combination. The data analysts can manipulate the ad data to the extent that they can, then work with more technical folks to go deeper and generate results that go beyond the analyst level of expertise.
The company, which has a 100 employees, plans to double that number in the in the next few months. That expansion will touch every department including helping customers with deployment and further building out the platform to add more features.
“We want to be the universal platform for data science where you can do anything you imagine for advanced data analytics,” Douetteau said.Featured Image: Ikon Images/Getty Images