The University of Buffalo leverages technology from Revolution R and IBM Netezza to drastically accelerate their research of the potential factors that may be contributing to Multiple Sclerosis, according to a case study the former published last week.

Revolution R develops a commercial version of the highly mathematical programming language after which the company was named. It adds a number of propriety elements to R including performance enhancements and Hadoop integration, as well as a server-side deployment framework.

The researchers at the University of Buffalo took advantage of these tweaks – along with the language’s natively broadened set of variables – to rewrite the tools they were using to analyze over 2,000 genetic and environmental factors that could be connected to MS. They took things a step further by tightly integrating with a Netezza data warehouse to centralize analytics  and reporting in one place, resulting in some fairly impressive performance and efficiency increases that Revolution proudly cited in its blog.

The computation of the various interactions between the thousands of different potential MS causes is now calculated 100 times faster, and Netezza speeds up individual workloads even more from 27.2 hours to only 11.7 minutes each.  Better yet, the new appliance is apparently cheaper to administrate than what the researchers were using prior to the upgrade.

“Now, using an IBM Netezza analytics appliance, in conjunction with software from Revolution Analytics, researchers can analyze disparate data in a matter of minutes instead of days, regardless of what type or size it is,” says an IBM spokesperson.  “The technology automatically consumes and analyzes the data, and makes the results available for further analysis, leaving researchers more time to analyze trends. “

IBM is definitely interested in making its big data storefront more appealing to the market.  Last week they acquired a search startup that, as it happens, originally started off as an academic initiative.