Introduction to R Visualizations with Power BI

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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:
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In this presentation hosted by Data Science Dojo, David Langer discussed:
• Understanding the nuances of how Power BI integrates with R, including necessary data pre-processing.
• Incorporating R visualizations into Power BI projects.
• A brief introduction to the R ggplot2 visualization package.
• A brief introduction to the R dplyr data wrangling package.
• Making R visualizations dynamic by responding to Power BI UX controls.
• How to engineer your R code for a cut-and-paste experience into Power BI.
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David is a veteran BI, analytics, and data science professional. He is currently the VP of Data Science at Data Science Dojo, focusing on growing the educational services practice. Previously, David was a Sr. Director for BI and Analytics at Microsoft where he managed a team that owned the mission-critical data platforms used to run Microsoft’s $10+ Billion supply chain. David's current passions are text analytics, event log mining, and mathematical programming. David holds a MS in Computer Science and a BA in Economics from the University of Washington.

For more videos and tutorials by David, visit his youtube channel.
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David's source code can be viewed and cloned from the Data Science Dojo GitHub meetup repository. Installation instructions for all data and software (e.g., which R packages are required) are available via the README file.
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