Revolution Analytics is proud to support local communities of R users by sponsoring qualified R user groups. To help foster the creation of new groups and the growth of existing groups, we offer the following sponsorship program. Each group's... Learn More
The Revolution R Enterprise Big Data Big Analytics (BDBA) platform super-charges organizations beyond the status quo in order to expedite discovery, accelerate growth and sharpen operations. It’s the... Learn More
The Revolution R Enterprise for SAS to R Users Quick Start Program is designed to address the areas of your existing program necessary for successful deployment and operation. A limited engagement that will provide:
Yale researchers Michael Kane, PhD and Casey King, PhD considered the FINRA rules through the lens of historical data analysis. By looking at roughly 24 billion trades from 2008-2010, the researchers studied the efficacy of the FINRA rules, as featured in the August 15, 2011 issue of Barrons. A timely analysis of market data on this massive scale poses serious computational challenges. In this webinar, three techniques are compared to meet the challenge:1. Parallel computing in R, highlighted by the use of the iterators and foreach packages.2. Cloud computing using Amazon Web Services3. A joint solution using IBM Netezza analytic appliances integrated with Revolution R Enterprise, an enterprise-ready distribution of R from Revolution Analytics.While each technique effectively meets the challenge of this massively parallel problem, the Netezza and Revolution R Enterprise solution has proven to bring analysis time down from a matter of months, to a matter of hours. Join the webcast to learn how these Yale Researchers were able to innovate their models and extend their analysis using the integrated solution.