20 Revolution Analytics Testimonials

"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."

"At the end of the day, our job isn’t about the programming and it isn’t about the system. It’s about getting the work done. I’m all in favor of the solution that lets me get the work done quickly and easily. We’ve been able to do something that we can’t really do otherwise. The speed is pretty remarkable."

"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 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 do that."

"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 delete variables in our model."

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

“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.”

“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 a problem that’s so big that most companies could not address it. If we had to go with a different solution we wouldn’t be as efficient as we are now.”

"After several years of data collection, crunching those numbers requires the use of a tremendous amount of memory at once. For that I use R Enterprise for 64-bit Windows. There are no limits on the amount of memory available. Prior to Revolution’s software development of R Enterprise for Windows, the only alternative was Linux, and that was just not practical."

"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 need a high-performance analytics infrastructure because marketing optimization is a lot like a financial trading. By watching the market constantly for data or market condition updates, we can now identify opportunities for our clients that would otherwise be lost."

"[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 simulations that drive our automated trading systems."

“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 it, they do contribute to it, and it’s in their own interests to promote it to other users and keep that growth going.”

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