DataRPM wants to make BI as conversational as Google search, raises $5.1M to make it possible
The word is out, big data is sexy. But as more and more businesses are turning to data analytics as a means of extracting business insights, the more clear it’s become that the first generation toolsets are woefully inadequate. There’s no shortage of data – companies have been stockpiling it for years – but going from that raw material to useful insights remains too cumbersome for mainstream adoption.
Businesses need two things to make the promise of big data a reality. With the era of the single data warehouse a thing of the past, users need tools to quickly and easily upload dynamic data from disparate sources into analytics platforms. Then, they need real-time and easy to interpret results delivered from these analytics platform, rather than the 90 to 180 days it often takes for companies relying on legacy BI solutions to get similar answers.
Washington, DC-based DataRPM has tackled these two problems head on with its “Cognitive BI” platform. The company uses a distributed computation search index, not unlike Google Search, rather than the industry standard data warehouse to make data more readily accessible and drastically reduce the time and cost of modeling semi-structured data. It then enables users to interact with the data through a natural-language question and answer interface and visualization layer that removes the need to learning SQL or other code-based querying methods.
“Data warehouses are where data goes to die,” says DataRPM CEO Sundeep Sanghavi. “What we’ve built is a single-stack solution that that simplifies business intelligence and makes extracting insights simple, intuitive, and possible in real-time.”
Just four months after announcing an $800,000 Seed round – nearly half of which remains in the bank – the company today announced a $5.1 million Series A round led by InterWest Partners with participation from existing investor CIT GAP Funds. DataRPM has been in beta since August 2013 and will use the funds to build out its team and prepare for the launch of its General Availability product slated for May of this year.
Through its early customer group, DataRPM has seen the greatest levels of early adoption within the financial services, communications, media, and software technology verticals, Sanghavi says. But while the company will surely court the Fortune 100, it’s the next 5,000 to 10,000 largest companies that represent the biggest opportunity, according to Interwest partner Khaled Nasr.
“We’ve seen plenty of other companies talk about solving this problem, but when we dug in there was no meat on the bone,” he says. “With DataRPM, it was different. They still have a lot to prove, but they’ve done an incredible amount in a short time with limited resources.”
As Nasr alludes, however, this is an extremely crowded space full of large and well-funded companies, making simply breaking through the noise represents a significant hurdle in itself. The Interwest partner believes that DataRPM’s beta users will be among its biggest evangelists and will likely set the ball rolling through word of mouth. From there, the company will need to continue delivering what it believes is a best-in-class solution to these core big data problems.
DataRPM’s single stack approach is different than many of its competitors which, often focus on solving a single problem rather than offering a comprehensive solution. For example, Trifacta offers a similar data cleansing and solution aimed at taming disparate semi-structured data sources. But the company does not combine that solution with an analytics engine and a visualization layer like DataRPM does, instead opting to integrate with existing BI solutions. In the past, businesses have been forced to adopt and cobble together numerous semi-integrated software solutions to satisfy their BI needs, leading to a costly, cumbersome, and often ineffective.
“They don’t just do a piece of the pie, but rather enable users ingest, clean up, index, search, and visualize data all within a single platform,” Nasr says. “There are pros and cons to focusing on solving a single problem, but we think the comprehensive approach makes sense when targeting mid-market, like DataRPM is. It makes it easy for customers to trial the service and get results right away, which helps with onboarding.”
DataRPM consists of a five-person US team, including three co-founders, plus a 20-person outsourced engineering team in Bangalore India. Sanghavi’s and his co-founders, CTO Shyamantak Gautam and CPO Ruban Phukan, are all experienced technologists with strategic and complementary backgrounds. Guatam previously in financial security for companies like JPMorgan & Chase, Charles Schwab, and the NYSE as well as on predictive analytics solutions for the telecom industry at Razorsight. Phukan has a search background including senior roles at Yahoo and founding Bixee.com, an Indian vertical search platform.As big data analytics becomes the norm, rather the exception, the companies enabling this transition stand to become the unicorns of this startup generation. DataRPM is a very small fish in a large and highly competitive pond. But with a new approach to data modeling and querying, the company is nothing if not distinct. We’ll soon see if this unique enough for the company to rise above the noise, or if Cognitive BI ends up being another passing fad.