20 Revolution Analytics Testimonials

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  • “The Revolution Analytics R framework and its seamless integration with solutions like IBM’s Netezza allow for rapid development and deployment of custom made high performance algorithms for big data analytics.”

  • "We began observing how much more quickly the open‐source community (in R and Python, specifically) was outpacing the analytical capacity of our commercial vendors. In an information and idea driven business, in which proprietary analytics are absolutely critical, we can’t afford to wait for commercial vendors to play catch‐up."

  • "De facto, R is already a significant component of Pfizer core technology. Access to a supported version of R will allow us to keep pace with the growing use of R in the organization, and provides a path forward to use of R in regulated applications."

  • “Sure there are other programming user groups in the quant finance world, but the community is certainly not like something I’ve ever seen in terms of just the amount of people. There’s a real collective sense of ownership for this thing. Because in the end, the data community does write …

  • "The Revolution R Enterprise 5.0 environment has delivered order of magnitude performance improvements, which has allowed our department to process four times the amount of analytics jobs. The researchers are now able to run, evaluate, modify and re-run their models multiple times to get more precise conclusions. It’s been amazing."

  • "[Revolution DeployR provides] a web service that is platform independent, easy-to-use and a standard for integration."

  • "We find two advantages to the Revolution Analytics and IBM framework: minimization of data transfer by moving the function to the data as well as the computation speedups associated with distribution of an embarrassingly parallel problem."

  • “There are a few important benefits [of Revolution R Enterprise]…It’s really easy to develop and maintain for analysts. We don’t need a full time DBA to administer the IBM database appliance and don’t need a hardcore programmer to deploy our prediction functions. We’ve been able to scale our solution to …