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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. Extending Power BI with Python and R
  2. Foreword
  3. Contributors
  4. About the author
  5. About the reviewers
  6. Preface
  7. Section 1: Best Practices for Using R and Python in Power BI
  8. Chapter 1: Where and How to Use R and Python Scripts in Power BI
  9. Chapter 2: Configuring R with Power BI
  10. Chapter 3: Configuring Python with Power BI
  11. Section 2: Data Ingestion and Transformation with R and Python in Power BI
  12. Chapter 4: Importing Unhandled Data Objects
  13. Chapter 5: Using Regular Expressions in Power BI
  14. Chapter 6: Anonymizing and Pseudonymizing Your Data in Power BI
  15. Chapter 7: Logging Data from Power BI to External Sources
  16. Chapter 8: Loading Large Datasets beyond the Available RAM in Power BI
  17. Section 3: Data Enrichment with R and Python in Power BI
  18. Chapter 9: Calling External APIs to Enrich Your Data
  19. Chapter 10: Calculating Columns Using Complex Algorithms
  20. Chapter 11: Adding Statistics Insights: Associations
  21. Chapter 12: Adding Statistics Insights: Outliers and Missing Values
  22. Chapter 13: Using Machine Learning without Premium or Embedded Capacity
  23. Section 3: Data Visualization with R in Power BI
  24. Chapter 14: Exploratory Data Analysis
  25. Chapter 15: Advanced Visualizations
  26. Chapter 16: Interactive R Custom Visuals
  27. Other Books You May Enjoy
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