20 Revolution Analytics Testimonials

"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."

"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."

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

"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."

"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."

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

"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 do that."