by Le Zhang (Data Scientist, Microsoft) and Graham Williams (Director of Data Science, Microsoft) As an in-memory application, R is sometimes thought to be constrained in performance or scalability for enterprise-grade applications. But by deploying R in a high-performance cloud environment, and by leveraging the scale of parallel architectures and dedicated big-data technologies, you can build applications using R that provide the necessary computational efficiency, scale, and cost-effectiveness. We identify four application areas and associated applications and Azure services that you can use to deploy R in enterprise applications. They cover the tasks required to prototype, build, and operationalize an enterprise-level data science and AI solution. In each of the four, there are R packages and tools specifically for accelerating the development of desirable analytics. Below is a brief introduction of each. Cloud resource management and operation Cloud computing instances…
Original Post: Services and tools for building intelligent R applications in the cloud