SAP has joined the list of big companies embracing the R language. SAP has committed it’s latest products including the in-memory device HANA and the newly launched Business Objects Predictive Analytics to be tightly integrated with the algorithms and statistical libraries available in R. Oracle has announced plans to make it’s own version of R called Oracle R Enterprise for better customization to analytics using Oracle databases. SAS Institute had made connectivity from SAS/IML and JMP products some time back. IBM‘s acquired analytics software SPSS had been one of the first software to work with R.
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SAP’s involvement with R has been different from other technology players. It has committed substantial technological resources to making it’s products compatible and in sync with R, while not marketing it with hype before the products were ready. SAP\s approach is two-pronged. With the SAP Business Objects Predictive Analytics suite, it ties in R’s strengths in statistics with a visual interface to create insights and analytics with much more ease than stand-alone software alone.
With the in-memory HANA appliance combined with the RHANA package, it helps to push data into HANA, and summarize and aggregate and analytically manipulate it there. Thus visual interface and in-memory processing for faster data operations on bigger data combine the strengths of R with none of it’s traditional weakness (esp regarding to bigger data). This creative mix and match of technologies enable SAP customers to have faster access to data, and easier interfaces to use it.
The SAP Business Objects Predictive Analysis was announced just this month. SAP Business Objects Predictive Analysis supports predictive analytic capabilities for pattern recognition, building predictive models with a Drag-and-drop visual interface for reduced model design time. SAP BusinessObjects Predictive Analysis is currently available and expected to be generally available later in 2012.
An interesting case study at https://allthingsbusinessanalytics.blogspot.in/ shows how SAP RHANA can help crunch huge amounts of data using HANA. The case study analyzed more than 200 million data points using SAP HANA and R and then brought in the aggregated results in HTML5 using D3, JSON and Google Maps APIs.
One of the most interesting things is that R is increasingly considered most suitable for big data analysis through cloud computing even though traditionally it had not be considered so suitable for bigger datasets on the desktop. The rationale for that is quite simple- R stores data in memory or in RAM. With memory and RAM prices increasingly cheap, and more than 4000 packages being made in R , it’s open source nature means that any big technology firm wishing to make a play in the lucrative market of business analytics can readily adopt and adapt R for its own use cases. To add to it, R plays well with Hadoop suite of technologies.
With almost all the big companies in the world of big data technology embracing R, this goes in a long way to convince people to start using R. Indeed knowledge of R seems to be a skill that is going to be increasingly in demand because it can be used with so many technological products. Indeed knowledge of R is already one of the most desirable skill sets that potential employers are looking for.
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