R is an open-source programming language that includes packages for advanced visualizations, Statistics, Machine Learning and much more.
SAP Analytics Cloud R Visualization feature allows users to integrate their own R environment into SAP Analytics Cloud.
The benefit of this is that people all over the world continue to invest a lot of time and energy into creating new and interesting types of statistical charts and graphs that you can use to analyze and present your data.
Another benefit of integrating R visualizations with SAP Analytics Cloud is that it’s flexible. You can change the chart type, characteristics, and depict your information in a variety of ways.
With this new integration in SAP Analytics Cloud, you can now:
- Insert R-visualizations into your story
- Interact with R-visualizations using SAP Analytics Cloud-controls (such as filters)
- Share these SAP Analytics Cloud stories, which include R-visualizations, with other users.
With the R visualization capability, users can perform statistical and analytical analyses and create truly captivating visuals to reflect these analyses.
Also, it is important to note that these visualizations remain interactive and consider the row-level security of users.
To add R visualizations to a story, you need to have an R server running and connected to SAP Analytics Cloud.
This connection is typically handled by an administrator and includes the server or host address, port number, certificate for encryption, and user credentials.
- Before we get started with our visualizations we can check a couple of things. First, make sure you are connected with an R Server.
- To do so your user must have admin rights. Otherwise, please ask your system admin user for help. Different options are available for example you may use your own R Server or use the SAP R Server. To do so go into the main menu and press “Administration” under the point “System”:
- Then proceed to “R Configuration” at the top of the screen. Check if you are connected to the SAP R sever runtime environment or to your remote R connection. If this is the case, we can proceed with our tutorial using the R Visualization in the SAC.
- Second, let’s have a look at our profile setting and make sure the number formatting is set to “1,234.56”. Otherwise, the dataset won’t be recognized correctly in the SAC.
Adding R Visualizations to Stories:
Once you have checked the connection, you can create a story from a data model already on SAP Analytics Cloud.
By choosing insert and R visualization, this allows you to indicate that you want to include a visualization as result from a script from R. It is important to indicate that you only can add visualization, but you can run any kind of R-script once you have validated the required libraries.
Which will generate the following frame on the Canvas. In the ‘Builder’-framework there are two important options:
- Input Data: to import the data into the R Visualization;
- Script: to use the R Script Editor, which applies the R Script on the imported data.
After having imported the data, using the ‘Add Script’-functionality will give the following consoles to work with:
- Editor: R Script should be incorporated here.
- Console: displays what is being executed (either successfully, or else it will display error messages).
- Environment: additional information, such as the name of the imported dataset.
- Preview: preview of the results of the R Script that has been added in the Editor framework.
R Visualizations Hands-On Examples:
Up and Down arrow based on KPI Values:
Pie Chart that would display Top 9 and group rest as “Others”:
Correlation – Scatter Plot:
Ranking – Dot Plot:
Now we have created R Visualizations in SAP Analytics Cloud.
Thank you for taking the time to read my blog and I hope you find it beneficial. Please like, share and comment 🙂