“R” you ready for agile advanced analytics?
In the world of healthcare, the use of advanced analytics to understand current performance and predict future outcomes is key to successfully navigating rapidly changing care and payment models. From managing quality to improving financial performance (both go hand-in hand), health systems are doubling down on investments in applied analytics.
Increasingly, a critical component in achieving success is the use of a specialized programming language called R.
R is the most widely used programming languages for statistical computing and predictive analytics that is increasingly favored by data scientists and clinical informaticists in developing the latest solutions for health analytics.
At Microsoft we are embracing and extending the use of R in healthcare worldwide. In the past year we did this by delivering a steady stream of innovations and updates to help our customers and partners leverage the power of R including:
- Our acquisition of Revolution Analytics, the leading commercial provider of software and services for R.
- Delivering SQL Server R Services as a built-in component of SQL Server 2016 CTP3.
- The introduction of Azure Machine Learning as a fully managed cloud service that enables the agile development and deployment of predictive analytics including machine learning with both R and Python.
This week we are excited to further extend Microsoft’s commitment to enterprise-grade R with the following announcements about our cross-platform offerings for enterprises:
- Revolution R Enterprise for Hadoop, Linux and Teradata is now available as Microsoft R Server with all the benefits of Microsoft’s enterprise support and purchasing options.
- The new Microsoft R Server Developer Edition will be available as a free download.
- Revolution R Open is now Microsoft R Open and is available to download for free.
With these releases, customers can use R with their platform of choice, both on-premises and in the cloud.
At Microsoft we are committed to making it easier for healthcare organizations, R developers and data scientists to cost effectively build applications and advanced analytics solutions at scale.
