Follow Datanami:
May 9, 2016

DataRobot Looks to Cut Data Science Backlog

The data science automation specialist DataRobot Inc. is gaining traction in the big data market for its machine-learning application as new investors like Intel Capital fund its expanding operations.

Boston-based DataRobot has so far raised more than $57 million in four equity investment rounds, including a $33 million funding round completed in February. Along with Intel Capital, Recruit Strategic Partners joined the startup’s fourth funding round as new investors.

The company’s machine-learning platform runs either on top of Hadoop as a cloud application or running on-premises. The startup founded in 2012 by CEO Jerry Achin and CTO Thomas DeGodoy targets its platform at data scientists with varying skill levels. Along with speeding the deployment of more accurate predictive models, the company said it is attempting to address the critical shortage of qualified data scientists while “changing the speed and economics of predictive analytics.”

The startup announced in March that its machine learning approach was certified on Cloudera Inc.’s enterprise platform for data management and analytics. Achin said the certification would help Hadoop users address the analytics backlog created by the data science skills gap. The certification also means Cloudera users could “incorporate automated machine learning into their big data analytics environment, with no additional interfaces, protocols or management skills required,” he asserted.

DataRobot also said the endorsement makes it the only Cloudera vendor partner certified on Apache Spark, YARN and CSDs (custom service descriptors) and Parcels, Cloudera’s mechanism for performing upgrades to packages installed on clusters with minimum hassles. The integration also uses Spark’s scalable machine learning library for in-memory data processing.

The inclusion of Spark support is timely given Cloudera’s “One Platform Initiative” launched last fall. The initiative is designed to close existing gaps between Spark and Hadoop while giving Spark the enterprise chops needed to be the default engine for workloads in Hadoop. That could help it take the mantle from MapReduce, which for years had been the go-to technology for a range of Hadoop frameworks.

Along with Cloudera, DataRobot’s clients also use databases and spreadsheet tools from data visualization and analytics vendors like Tableau Software. While the market for visualization and storage products has softened in recent months, DataRobot is betting that most enterprises still have a backlog of data science projects that could be addressed via its machine learning approach.

Meanwhile, the company is using its latest cash infusion to expand its U.S. and overseas operations, including footholds in France, the U.K., Japan and Singapore. It recently moved to a new 31,000 square foot office space in the heart of Boston’s financial district. As of late winter, DataRobot’s head count totaled more than 100 and it has about 60 open positions (revealing there may also be a skills gap related to closing the skills gap).

The company’s clients reportedly include major banks and insurers as well as other smaller businesses. New York Life is an early investor.

Recent items:

Machine-Learning Platform Certified For Cloudera

Spark is the Future of Hadoop, Cloudera Says