Azure ML Studio, the collaborative drag-and-drop data science workbench, now supports R 3.4 in the Execute R Script module. Now you can combine the built-in data manipulation and analysis modules of ML Studio with R scripts to accomplish other data tasks, as for example in this workflow for oil and gas tank forecasting.
With the Execute R Script module you can immediately use more than 650 R packages which come preinstalled in the Azure ML Studio environment. You can also use other R packages (including packages not on CRAN) and source in R scripts you develop elsewhere (as shown above), although this does require the time to install them in the Studio environment. You can even create custom ML Studio models encapsulating R code for others to use in the drag-and-drop environment.
If you're new to Azure ML Studio, check out the Quickstart Tutorial for R to learn how use the Execute R Script module, and to check out what's new in the latest update follow the link below.
Microsoft Docs: What's New in Azure Machine Learning Studio