Microsoft has acquired big data firm Revolution Analytics for an undisclosed fee, as the software giant looks to bring the R programming language, often used for statistical analysis, to more companies.
Revolution Analytics' R-based solutions are already used by some of the world’s largest banks and financial services, as well as pharmaceutical companies and the manufacturing industry.
Microsoft’s corporate vice president of machine learning, Joseph Sirosh, explained how the acquisition will help expand the reach of Revolution Analytics.
“By leveraging Revolution Analytics technology and services, we will empower enterprises, R developers and data scientists to more easily and cost effectively build applications and analytics solutions at scale,” he wrote in a blog post.
"We are excited to help foster the open source evolution of R and, particularly, the community of people that drives that evolution. We will continue to support and evolve both open source and commercial distributions of Revolution R across multiple operating systems."
David Smith, Revolution Analytics chief community officer, admitted that Microsoft may seem like an unnatural partner for an open-source company at first, but that the Redmond-based company’s CEO Satya Nadella continues to embrace open-source platforms such as Linux.
“Microsoft has been an active participant in many other open source projects, too,” he said. “There are over 1,600 OSS projects from Microsoft on CodePlex and GitHub. Microsoft engineers have actively contributed to the Linux kernel for years, and the company has contributed to open source community projects including Chef, Puppet, Docker, MongoDB, Redis and OpenJDK.”
Mr Sirosh signed off by expressing his own personal enthusiasm for statistical analysis and the work carried out by Revolution Analytics.
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“As a data scientist and longtime R enthusiast, I am incredibly excited about Revolution Analytics technology and employees joining Microsoft,” he said. “I firmly believe that we are at the threshold of a revolution in information technology driven by the use of statistics and scientific analyses on big data.”