Incorporating advanced analytics into regular Business Intelligence processes used to be a monumental task. This changed in 2015 when Microsoft acquired R, one of the rapidly growing programming languages for data science and machine learning. With this acquisition, Microsoft has been able to support R with open source improvements and custom functionality enhancements that businesses can easily deploy using R Server.
Because of this, R has jumped in popularity. According to IEEE rankings, it moved from #9 to #5 between 2014 and 2016.
What are some of these improvements Microsoft provided and how did this change the game providing advanced analytics? Microsoft identified a few bottlenecks with current advanced analytics and worked to address those issues further by providing some key functionality:
- Flexibility: Apply flexible analytics to multiple platforms ranging from traditional to cutting edge. With R Server you can run in-database analytics in Microsoft SQL Server and Teradata. You also have the capability to run predictive R models on Windows, Linux, Hadoop, or Spark in order to leverage big data architecture and scale out processing
- Open Source combined with Microsoft (when needed!): With R, you get many of the same open source packages actively being developed and improved in the open source community, but can also bring in some of the more innovative R packages such as RevoScaleR and MicrosoftML.
- Deployment: Train your models on one platform, and deploy in another. No need to rewrite the underlying language or configure for scale out capabilities.
- Speed: Microsoft has made improvements to real-time scoring to enable up to 1 million predictions per second in some cases and supports many batch scoring improvements.
- Web API ease-of-use: Easily deploy your R code as a Web API to be called for prediction capabilities
There are more than a few use cases that can easily be addressed by using the analytic capabilities provided by Microsoft R Server. If you'd like to see a demo and hear more about Microsoft R Server, register for my webinar on June 15.