You can now use Alteryx Designer, the data science workflow tool from Alteryx, as a drag-and-drop interface for many of the big-data statistical modeling tools included with Microsoft R. Alteryx v11.0 includes expanded support for Microsoft SQL Server 2016, Microsoft R Server, Azure SQL Data Warehouse, and Microsoft Analytics Platform System (APS), with new workflow tools to access functionality without having to write R code manually.
Alteryx V11 adds a new XDF Input tool (and corresponding XDF Output tool) to bring data into Alteryx using the Microsoft R out-of-memory file format. In addition, you can use several other new tools to train statistical models on that data, without needing to bring the data into Alteryx itself (only the meta-data is passed from one node to the next). The models provided include:
- Boosted Model
- Count Regression
- Decision Tree
- Forest Model
- Gamma Regression
- Linear Regression
- Logistic Regression
along with the ability to use stepwise methods to select variables, and scoring (prediction) using trained models.
To use Microsoft R with Alteryx, you will first need to download and install the version of Alteryx Predictive Tools corresponding with the version of R you have installed. Alteryx provides versions for both Microsoft R Server and the free Microsoft R Client, as well as open source R 3.3.2.
For more on the integration of Alteryx with Microsoft R, check out the blog post linked below.
Alteryx Community: Alteryx V11.0 Integrates with Microsoft