“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 …

"There are lots of good reasons to use Revolution Analytics in a super computer like Netezza. It’s faster and easier to program. It will speed up our computation. And, we have more data sets available to us because of how flexible and quick Revolution Analytics makes it to add and …

"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."

"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."

“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.”

"Once you know what is driving your marketing, you can better direct what treatments you are using for specific people."

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

"There is so much information out there that can make a quant’s life difficult. Revolution R Enterprise just works. It's like using standard R, but lets me use all 32GB of memory on my 64-bit Windows system. Without OneTick Database integrated with Revolution R, I simply could not do the …

“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 …

"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."

"Northern Trust went to Revolution Analytics and asked if we could explore the opportunity to parallelize our Monte Carlo simulations."

"Revolution R is faster than regular R. The faster we can analyze data, the less time it takes us to build our diagnostic algorithms."

"I use [Revolution R Enterprise] for building prototypes because it’s fast and easy to make adjustments. I can build the prototype and just let it run, because it’s very fast!"

"We see a lot of potential in Revolution’s big data package. In the past, people would say that R couldn’t handle big data. That was the number one excuse for not using R. Well, now R can handle big data because Revolution is tackling the problem."

"We use R for adaptive designs frequently because it’s the fastest tool to explore designs that interest us. Off-the-shelf software, gives you off-the-shelf options. Those are a good first order approximation, but if you really want to nail down a design, R is going to be the fastest way to …