Ingest, transform, manipulate, and visualize your data beyond Power BI's capabilities.

Key Features

• Discover best practices for using Python and R in Power BI by implementing non-trivial code
• Enrich your Power BI dashboards using external APIs and machine learning models
• Create any visualization, as complex as you want, using Python and R scripts

Book Description

The latest edition of this book delves deep into advanced analytics, focusing on enhancing Python and R proficiency within Power BI. New chapters cover optimizing Python and R settings, utilizing Intel's Math Kernel Library (MKL) for performance boosts, and addressing integration challenges. Techniques for managing large datasets beyond available RAM, employing the Parquet data format, and advanced fuzzy matching algorithms are explored. Additionally, it discusses leveraging SQL Server Language Extensions to overcome traditional Python and R limitations in Power BI. It also helps in crafting sophisticated visualizations using the Grammar of Graphics in both R and Python.

This Power BI book will help you master data validation with regular expressions, import data from diverse sources, and apply advanced algorithms for transformation. You'll learn how to safeguard personal data in Power BI with techniques like pseudonymization, anonymization, and data masking. You'll also get to grips with the key statistical features of datasets by plotting multiple visual graphs in the process of building a machine learning model. The book will guide you on utilizing external APIs for enrichment, enhancing I/O performance, and leveraging Python and R for analysis.

You'll reinforce your learning with questions at the end of each chapter.

Table of Contents

Chapter 1: Where and How to Use Rand Python Scripts in Power Bl

Chapter 2: Configuring R with Power Bl

Chapter 3: Configuring Python with Power Bl

Chapter 4: Solving Common Issues When Using Python and R in Power Bl

Chapter 5: Importing Unhandled Data Objects

Chapter 6: Using Regular Expressions in Power Bl

Chapter 7: Anonymizing and Pseudonymizing Your Data in Power Bl

Chapter 8: Logging Data from Power Bl to External Sources

Chapter 9: Loading Large Datasets Beyond the Available RAM in Power Bl

Chapter 10: Boosting Data Loading Speed in Power Bl with Parquet Format

Chapter 11: Calling External AP ls to Enrich Your Data

Chapter 12: Calculating Columns Using Complex Algorithms: Distances

Chapter 13: Calculating Columns Using Complex Algorithms: Fuzzy Matching

Chapter 14: Calculating Columns Using Complex Algorithms: Optimization Problems

Chapter 15: Adding Statistical Insights: Associations

Chapter 16: Adding Statistical Insights: Outliers and Missing Values

Chapter 17: Using Machine Learning without Premium or Embedded Capacity

Chapter 18: Using SQL Server External Languages for Advanced Analytics and ML Integration in Power Bl

Chapter 19: Exploratory Data Analysis

Chapter 20: Using the Grammar of Graphics in Python with plotnine

Chapter 21: Advanced Visualizations

Chapter 22: Interactive R Custom Visuals

Review

“I posted about the first edition of this book back in 2021. This new edition has several new chapters on optimizing R and Python settings, using Intel’s Math Kernel library for performance, and addressing integration challenges. These are fascinating things that no one else in the Power BI world is talking about. I feel like a future third edition, covering what will be possible with Power BI and Python in Fabric in the next 2-3 years, will be really cool”

Chris Webb

Principal Program Manager at Microsoft

“Luca has a gift for clearly explaining complex topics, and he effectively uses screenshots, diagrams, and visuals to provide clear exposition. Before reading this book, I had Power BI in my toolbox, but often took other routes for complex statistical analyses. However, thanks to this book, I now use Power BI as my complete analytics hub. This new edition has over 200 pages of excellent new material, and if you are an intermediate to advanced Power BI user, I will highly recommend this book.”

Brian Julius, Power BI Expert

“Extending Power BI with Python and R is a comprehensive and practical guide for enhancing data analysis capabilities in Power BI. With detailed explanations, practical examples, and step-by-step instructions, this book is an essential resource for anyone looking to integrate R and Python into their Power BI workflows. Whether you're a beginner or an experienced user, this book provides valuable insights and practical tips for maximizing the potential of Power BI. As an avid bookworm, having read more than 30 books on the Microsoft Power Platform, this one is a must for anyone who works with Power BI. Highly recommended guys!”

Thomas Rice, PMP, Senior IT Application Project Manager at EMCOR Facilities Services

“While Python and R are definitely not my primary area of interest, it doesn't mean I'm not enjoying reading about these two - especially when they are being used in synergy with my favorite tool, Power BI! So, after I've read the 1st edition of Extending Power BI with Python and R, written by my friend Luca Zavarella, I was excited to get my hands on the 2nd edition of the book. And, it (again) lives to its high expectations. Although I probably won't use Python/R in every Power BI solution, it's still extremely useful to know when to leverage them to, as the book title suggests, extend Power BI beyond standard set of features. Great work, Luca!”

Nikola Ilic, MVP Data Platform, Founder of Data Mozart, and instructor and author at O’Reilly

“I’ve had the opportunity to review the second edition of the book, Extending Power BI with Python and R by Luca Zavarella, and I must say, it's a game-changer! The authors focus on practical, real-world applications. Whether you're looking to perform advanced analytics, create custom visuals, or automate workflows, this book has you covered. Each chapter is well-structured, offering step-by-step instructions and examples. Luca Zavarella brings his extensive experience to the table, sharing valuable insights and best practices that you won't find elsewhere. He builds on the first edition of the book to include new ways to visualize complex data using the grammar of graphics in both R and Python in this second edition.

If you're serious about maximizing the potential of Power BI, "Extending Power BI with Python and R" is a resource you cannot afford to miss. It’s not just about adding new tools to your arsenal; it's about transforming how you approach data analytics.”

Bernard Obeng Boateng, Microsoft MVP, Lead Trainer at Finex Skills Hub

“This is another very comprehensive book and took quite a while to read. And another one where I can't imagine how long it must have taken to write. It will be a vital reference for anyone trying to apply Python and/or R in Power BI. In this book, Luca's experience shines through. The second edition adds great value. Anyone with an interest in applying advanced analytics in Power BI should check it out. You will learn a lot.”

Dr. Gregory Low, Founder and Principal Mentor at SQL Down Under - Long-term Microsoft MVP, and member of the Regional Director Program



About the Author

Luca Zavarella has a rich background as an Azure Data Scientist Associate and Microsoft MVP, with a Computer Engineering degree from the University of L'Aquila. His decade-plus experience spans the Microsoft Data Platform, starting as a T-SQL developer on SQL Server 2000 and 2005, then mastering the full suite of Microsoft Business Intelligence tools (SSIS, SSAS, SSRS), and advancing into data warehousing. Recently, his focus has shifted to advanced analytics, data science, and AI, contributing to the community as a speaker and blogger, especially on Medium. Currently, he leads the Data & AI division at iCubed, and he also holds an honors degree in classical piano from the "Alfredo Casella" Conservatory in L'Aquila.