Advanced Analytics in Power BI with R and Python: Ingesting, Transforming, Visualizing

Advanced Analytics in Power BI with R and Python is a practical, code-forward guide for readers who want to do more with Power BI than the built-in interface allows. Ryan Wade focuses on the real work of analytics: building custom visuals, pulling data in from multiple sources, transforming it cleanly, and pushing further into machine learning and AI workflows.

Power BI, R, and Python working together

The book is built around a simple but powerful idea: R and Python can fill the gaps where native Power BI tools become limiting. That makes this a useful title for analysts and data professionals who want more control over visualization, shaping data, and automating repeated tasks without leaving the Power BI ecosystem.

What the book covers

• Creating custom data visualizations in R with ggplot2
• Ingesting data from sources such as CSV, Excel, SQL Server, and APIs
• Transforming data with advanced string handling and calculated columns
• Applying machine learning and AI techniques within Power BI workflows
• Productionizing data science models and wrangling scripts for practical use

A hands-on structure

The table of contents shows a very implementation-focused approach. Rather than staying abstract, the chapters move through recipes and worked examples that connect data preparation, visualization, and analytics in a sequence readers can follow and adapt.

Who will get the most from it

This ebook is best suited to business analysts, data analysts, data scientists, and Power BI users who already know the basics and want a stronger technical toolkit. If you are looking for a book that treats Power BI as a platform for scripting and analytics rather than just dashboard building, this one belongs on your shortlist.

Why it stands out

By combining Power BI with R and Python, the book opens up techniques that are awkward or impossible with native tools alone. That combination makes it especially appealing for readers who want cleaner workflows, more flexible visuals, and a more analytical approach to reporting. 📊