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.

• 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 -series data
  
• Create any visualization, as complex as you want, using R scripts
  

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.

• Where and How to Use R and Python Scripts in Power BI
  
• Configuring R with Power BI
  
• Configuring Python with Power BI
  
• Importing Unhandled Data Objects
  
• Using Regular Expressions in Power BI
  
• Anonymizing and Pseudonymizing Your Data in Power BI
  
• Logging Data From Power BI To External Sources
  
• Loading Large Datasets Beyond the Available RAM in Power BI
  
• Calling External APIs to Enrich Your Data
  
• Calculating Columns Using Complex Algorithms
  
• Adding Statistics Insights: Associations
  
• Adding Statistics Insights: Outliers and Missing Values
  
• Using Machine Learning Without Premium or Embedded Capacity
  
• Exploratory Data Analysis
  
• Advanced Visualizations
  
• Interactive R Custom Visuals
  

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