May 14, 2012
Multiple sclerosis (MS) is a chronic neurologic disorder that afflicts many in the primes of their lives. The biomedical research community has ramped up its use of big data analytics to illuminate the myriad factors that contribute to the onset and progression of MS. On April 26, IBM announced that the State University of New York (SUNY) Buffalo is using tools from our Netezza portfolio and from our big data analytics business partner, Revolution Analytics, for their ongoing MS research initiative. We have recently published blogs on the effort, by Steve Hamm, Mike Kearney, and yours truly.
May 9, 2012
Further to news of SUNY’s exploration of big data to understand possible causes of multiple sclerosis, I spoke with David Smith, VP of Marketing at Revolution Analytics, for a briefing on some advantages of R for analysis of large data sets.
February 27, 2012
The buzz around big data is driving further interest in the entire analytics market. Applying analytics to big data is the driver behind creating new, game-changing business value for enterprises. New analytic techniques and tools are being introduced into the enterprise to help spur on the big data analytic challenges. At a market buzz level, many of these tools and approaches appear equivalent, but when you start to look into the details there are distinct benefits, both today and with the direction these tools are taking in the future, that will constrain your big data analytic capabilities.