Power BI can do more than its built-in tools alone. In Extending Power BI with Python and R, Luca Zavarella shows how analytical languages fit into the platform’s data workflows—from loading and transforming data to building visualizations and exploring more advanced analytical problems.
Bring Python and R into your Power BI workflow
The book begins with where scripts can be used in Power BI and how they interact with data. It then covers configuring R and Python for Power BI, including development environments, compatibility, and practical limitations. That grounding helps readers understand not just how to add a script, but where it belongs and what to consider when it runs.
Work through real data challenges
Later chapters explore a broad set of applications: regular expressions for validating and extracting data, anonymization and pseudonymization, logging, large datasets, Parquet, external APIs, fuzzy matching, optimization, and statistical analysis. The examples connect Python and R techniques to familiar business intelligence tasks, giving readers ways to think through problems that may exceed standard Power BI features.
Go beyond standard reporting
Machine learning, exploratory data analysis, and visualization receive attention too, including approaches to the Grammar of Graphics in Python and advanced visualizations. The book also discusses integration issues and concludes its chapters with questions that let readers revisit key concepts.
For Power BI practitioners ready to extend their toolkit
This second edition is written for business analysts, BI professionals, and data scientists who already use Power BI. Working knowledge of Power BI is important; some familiarity with Python and R is helpful as well. For readers looking to combine those languages with their existing reporting and analysis work, this book offers a substantial, practical reference. 💻
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