Production environment choice - R / Python / SAS?



I have about 7 years of experience in analytics and data science. I have primarily used SAS in my professional experience and R / Python in personal capacity (mainly in Kaggle competitions).

While R and Python (especially iPython notebooks) are both great languages to perform targeted analysis and have libraries for cutting edge algorithms, I have not seen a production environment using R / Python for making instantaneous decisions (e.g. Credit card applications approval, fraud detection)

Can any one provide examples / case studies of real life case studies on R / Python? Also, what are the challenges and benefits of using it over SAS?

Machine learning using SAS vs Python


There is nothing like SAS is the only software in production environment. There are several case studies on R available on Revolution Analytics showcasing use of R to solve various problems. Here is an example link:

There are companies building data science products based on R and Python - for example Shiny, yhat and datarobot.

I think your experience might be limited to a particular domain / industry / geography. For example, Python is the choice of language for companies like Google, Evernote, Dropbox. While they are not dealing with credit card approvals, they definitely detect a lot of fraud at their end.