Microsoft’s Power BI is a powerful technology for quickly creating rich visualizations. Power BI has many practical uses for the modern data professional including executive dashboards, operational dashboards, and visualizations for data exploration/analysis.
Microsoft has also extended Power BI with support for incorporating R visualizations into Power BI projects, enabling a myriad of data visualization use cases across all industries and circumstances. As such, Power BI is an extremely valuable tool for any Data Analyst, Product/Program Manager, or Data Scientist to have in their tool belt.
At the meetup for this topic presenter David Langer showed how Power BI can be extended using R visualizations to achieve analyses that are difficult, or not possible, to achieve with out of the box Power BI features.
A primary focus of the talk were a number of “gotchas” to be aware of when using R Visualizations within Power BI projects:
- Power BI limits data passed to R visualizations to 150,000 rows.
- Power BI automatically removes duplicate rows before passing data to Power BI.
- Power BI allows for permissive column names that can cause difficulties in R code.
David also covered best practices for using R visualizations within Power BI projects, including using R tools like RStudio or Visual Studio R Tools to make R visualization development faster. A particularly interesting aspect of the talk was how to engineer R code to allow for copy-and-paste from RStudio into Power BI.
The talk concluded with examples of how R visualizations can be incorporated into a Power BI project to allow for robust, statistically valid analyses of aggregated business data. The following visualization is an example from the talk: