Microsoft finalises acquisition of Revolution Analytics
Microsoft has officially closed an acquisition agreement with Revolution Analytics, the statistical software company behind the open source software ‘R’ for enterprise, academic and analytics customers. The company says it will continue to support the commercial distributions of the Revolution R software.
The agreement will allow Microsoft to use the R language for advanced analytics on big data, says Joseph Sirosh, Microsoft corporate vice president information management and machine learning.
It enables Microsoft to bring enterprise grade R implementations to on-premise, hybrid and cloud environments.
The acquisition of Revolution will also enable Microsoft to help close the data scientist and analytics skills gap, says Sirosh.
He says Microsoft will ‘carry forward’ Revolution’s efforts to educate and train developers and data scientists who want to learn R, leveraging its global programmes and partner ecosystem.
Sirosh says, Microsoft plans on building R and Revolution’s technology into the company’s data platform products, which will target companies, developers and data scientists working on-premises, hybrid cloud and Azure public cloud environments, allowing customers and partners to take better advantage of R.
For instance, Microsoft will build R into SQL Server to provide in-database analytics that can be deployed in any of the aforementioned environments.
The company will also integrate Revolution’s scalable R distribution into Azure HDInsight and Azure Machine Learning, and will continue to support running Revolution R Enterprise across heterogeneous platforms including Linux, Teradata and Hadoop deployments.
“We are excited to foster the open source evolution of R fueled by its active, passionate community.
“We are excited to support and amplify Revolution’s open source projects such as the fast Revolution R Open distribution, the ParallelR collection of packages for distributed programming, Rhadoop for running R on Hadoop nodes, DeployR for deploying R analytics in web and dashboard applications, the Reproductible R Toolkit and RevoPemaR for writing parallel external memory algorithms.
“We will continue to support and evolve these and the commercial distributions of Revolution R across multiple operating systems,” says Sirosh.
Currently, R is used by over two million people globally and by a number of enterprises.
R, the programming language, has been targeted for the enterprise and is capable of speed and scalability, says Sirosh.
According to Sirosh, its parallel external memory algorithms, Revolution R Enterprise is capable of delivering speeds 42 times faster than competing technology from SAS.