R scripts cannot directly access Power BI data models (e.g., the data stored in Power BI’s internal Data Model such as tables, relationships, and measures). However, you can interact with the data in Power BI through the following approaches:
1. Using R Scripts to Access Power BI Data Visualizations:
-
When you create R visuals in Power BI, you can only access the data that has been passed to the visualization layer (i.e., the data that is part of the table visualized). The dataset is passed to the R script when the user interacts with the visual, not from the underlying data model directly.
-
R scripts in visuals do not have access to the entire Power BI model, but they receive the data that’s being used in the visual. This means that you can manipulate the filtered or aggregated data that is displayed in a visual, not the raw data in the data model.
2. Using R in Power Query (Data Transformation):
-
R scripts can be used in Power Query to manipulate data during the data import and transformation process (before it’s loaded into the Power BI model). This allows you to clean, transform, or preprocess data before it becomes part of the Power BI data model.
-
You can add an R script step in Power Query Editor by using the "Run R Script" option. This script can process the data you’ve loaded or connected to in Power BI and then transform it before it enters the data model.
3. Using R for Analysis on Imported Data:
-
If you need to access data already loaded into Power BI for analysis, you can use R to perform statistical or visual analysis on the data through R visuals in Power BI.
-
You can use the Data Model in Power BI to create tables and perform calculations using DAX, and then pass these results as input to R visuals. However, R cannot directly interact with DAX measures or calculated columns once they’re loaded in the model unless they are explicitly passed into the visual.
4. Workaround: Using External Data Sources:
-
Export Data from Power BI: You can export data from Power BI visuals to an external file (e.g., Excel, CSV) and then load this file into R for further processing. However, this is an external workaround and may not be real-time or efficient for large datasets.
-
Using Power BI API: Another workaround would be to use the Power BI REST API or Power BI Service to programmatically access dataset information from Power BI and then manipulate or analyze it using R externally. This requires external tools and scripting to integrate the Power BI data model with R.
