SAS continues to expand analytics options with additional R integration
SAS supports integrated analytics, fuels success
SAS GLOBAL FORUM, SEATTLE (12 Apr. 2010) – SAS, the leader in business analytics, expands analytics options for customers with the announcement of additional interfaces to the R open-source statistical computing language for both SAS/IML® and JMP®. These new enhancements exemplify the flexibility that SAS provides customers to build a dynamic and extensible analytics framework. With SAS, organizations can drive more value from data than ever before.
In 2009, SAS integrated R with SAS/IML Studio. With the release of JMP 9 software this September, new integration with R will enable its users to display analytic results leveraging JMP’s interactive graphics, while allowing R users access to JMP and SAS Analytics. The new integration will also let R programmers build user interfaces to deliver their programs to a much broader audience.
Verifying analyses at Abbott Global Pharmaceutical
“I’m very positive about the new R interface, which lets me consolidate my analytics work in JMP,” said Dave LeBlond, PhD, Principal Research Statistician, Abbott Global Pharmaceutical R&D. “I have the power of JMP exploratory tools to begin the analysis. Then, I can bring in specialized, nontraditional Bayesian tools from the R environment. Finally, I can verify convergence and summarize results with JMP analysis and graphics without having to document code from multiple platforms. This is an important addition to JMP.”
The next release of SAS/IML will extend R integration to the server environment – enabling users to deploy results in batch mode and access R from SAS on additional platforms, such as UNIX and Linux.
“We’re making it easier for customers to use R with SAS,” said Radhika Kulkarni, SAS Vice President of Advanced Analytics. “SAS provides the world’s most extensible and flexible environment for analytics. SAS’ ongoing commitment is to provide more analytics options for customers, enabling them to apply proven algorithms in SAS alongside specialized methods in R. Matching up analytic capabilities to meet problems and opportunities fuels innovation and success.”
SAS has long supported open architectures such as Linux, languages such as Java, and industry standards such as PMML. More recently, SAS has enabled customers to execute analytical models and deploy results directly inside of key databases. The depth and breadth of SAS Analytics – coupled with award-winning customer support – lets organizations thrive despite constrained resources.
SAS documentation and technical support: priceless
Customers such as BioMimetic, which develops products that promote healing of musculoskeletal injuries and diseases, experience SAS’ dedication to analytics excellence firsthand. Impressed by SAS’ superior analytics, BioMimetic made SAS an integral part of their analysis and delivery framework.
“Every week we get new questions that demand serious data analysis,” said Rafe Donahue, PhD, Associate Director of Statistics at BioMimetic Therapeutic. “SAS gives us the capacity and support to answer them, SAS’ complete documentation and live technical support is priceless. In our highly regulated environment, the R&D, validation and verification behind SAS give me great confidence in the computations I do with [its] applications.”SAS Global Forum
JMP 9 brings the interactive graphics and deep statistics of JMP to R users to enhance the analytic experience by providing flexible, dynamic visualizations.