Extending Power BI with Python and R: Ingest, transform, enrich, and visualize data using the power of analytical languages

Extending Power BI with Python and R: Ingest, transform, enrich, and visualize data using the power of analytical languages book cover

Extending Power BI with Python and R: Ingest, transform, enrich, and visualize data using the power of analytical languages

Author(s): Luca Zavarella (Author)

  • Publisher: Packt Publishing
  • Publication Date: 26 Nov. 2021
  • Language: English
  • Print length: 558 pages
  • ISBN-10: 1801078203
  • ISBN-13: 9781801078207

Book Description

Perform more advanced analysis and manipulation of your data beyond what Power BI can do to unlock valuable insights using Python and R

Key Features

  • Get the most out of Python and R with Power BI by implementing non-trivial code
  • Leverage the toolset of Python and R chunks to inject scripts into your Power BI dashboards
  • Implement new techniques for ingesting, enriching, and visualizing data with Python and R in Power BI

Book Description

Python and R allow you to extend Power BI capabilities to simplify ingestion and transformation activities, enhance dashboards, and highlight insights. With this book, you'll be able to make your artifacts far more interesting and rich in insights using analytical languages.

You'll start by learning how to configure your Power BI environment to use your Python and R scripts. The book then explores data ingestion and data transformation extensions, and advances to focus on data augmentation and data visualization. You'll understand how to import data from external sources and transform them using complex algorithms. The book helps you implement personal data de-identification methods such as pseudonymization, anonymization, and masking in Power BI. You'll be able to call external APIs to enrich your data much more quickly using Python programming and R programming. Later, you'll learn advanced Python and R techniques to perform in-depth analysis and extract valuable information using statistics and machine learning. You'll also understand the main statistical features of datasets by plotting multiple visual graphs in the process of creating a machine learning model.

By the end of this book, you’ll be able to enrich your Power BI data models and visualizations using complex algorithms in Python and R.

What you will learn

  • Discover best practices for using Python and R in Power BI products
  • Use Python and R to perform complex data manipulations in Power BI
  • Apply data anonymization and data pseudonymization in Power BI
  • Log data and load large datasets in Power BI using Python and R
  • Enrich your Power BI dashboards using external APIs and machine learning models
  • Extract insights from your data using linear optimization and other algorithms
  • Handle outliers and missing values for multivariate and time-series data
  • Create any visualization, as complex as you want, using R scripts

Who this book is for

This book is for business analysts, business intelligence professionals, and data scientists who already use Microsoft Power BI and want to add more value to their analysis using Python and R. Working knowledge of Power BI is required to make the most of this book. Basic knowledge of Python and R will also be helpful.

Table of Contents

  1. Where and How to Use R and Python Scripts in Power BI
  2. Configuring R with Power BI
  3. Configuring Python with Power BI
  4. Importing Unhandled Data Objects
  5. Using Regular Expressions in Power BI
  6. Anonymizing and Pseudonymizing Your Data in Power BI
  7. Logging Data From Power BI To External Sources
  8. Loading Large Datasets Beyond the Available RAM in Power BI
  9. Calling External APIs to Enrich Your Data
  10. Calculating Columns Using Complex Algorithms
  11. Adding Statistics Insights: Associations
  12. Adding Statistics Insights: Outliers and Missing Values
  13. Using Machine Learning Without Premium or Embedded Capacity
  14. Exploratory Data Analysis
  15. Advanced Visualizations
  16. Interactive R Custom Visuals

Editorial Reviews

Review

"R and Python integration in Power BI have been around for years but this book goes beyond the superficial aspects. Mainly focusing on advanced analytics and data science, Luca provides an experienced practitioner’s point of view on this broad topic, compared to a "canonical" Power BI developer. If you work with Power BI on a daily basis, you will discover innovative new approaches throughout this book. Many arcane parts of R and Python integration will be made much more clear. Data analysts often "accidentally meet" R and Python during their journey through Power BI and this book provides a solid base on how to get the best of both worlds, to solve problems and add value to data with very detailed scenarios using a step-by-step approach that the reader can replicate easily."-- Riccardo Perico, BI & Power BI Engineer, Microsoft Data Platform MVP

"This book is a must-have for any Power BI developer explaining in a clear manner how to do things that were difficult or impossible in Power BI without Python or R. This book is packed full of great content and also explores regular expressions, calling APIs, using machine learning models and advanced visualization in Power BI." -- Leon Gordon, Microsoft Data Platform MVP and Director Of Analytics at Onyx Data

"The book does a good job of explaining how Python and R allow you to do things that are difficult or impossible otherwise. There are chapters on regular expressions, calling APIs, using machine learning models and advanced visualisations. I haven’t seen any other books, videos or blog posts that cover these topics in such detail, so if you have some Python or R skills and want to make use of them in Power BI, this book seems to be a good bet." -- Chris Webb, Principal Program Manager on the Power BI Customer Advisory Team

About the Author

Luca Zavarella is certified as an Azure Data Scientist Associate and is also a Microsoft MVP for artificial intelligence. He graduated in computer engineering at the Faculty of Engineering of L'Aquila University, and he has more than 10 years of experience working on the Microsoft Data Platform. He started his journey as a T-SQL developer on SQL Server 2000 and 2005. He then focused on all the Microsoft Business Intelligence stack (SSIS, SSAS, SSRS), deepening data warehousing techniques. Recently, he has been dedicating himself to the world of advanced analytics and data science. He also graduated with honors in classical piano at the Conservatory "Alfredo Casella" in L'Aquila.

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