Book Image

Extending Power BI with Python and R

By : Luca Zavarella
Book Image

Extending Power BI with Python and R

By: Luca Zavarella

Overview of this book

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.
Table of Contents (22 chapters)
1
Section 1: Best Practices for Using R and Python in Power BI
5
Section 2: Data Ingestion and Transformation with R and Python in Power BI
11
Section 3: Data Enrichment with R and Python in Power BI
17
Section 3: Data Visualization with R in Power BI

Chapter 13: Using Machine Learning without Premium or Embedded Capacity

Thanks to the computing power now available via powerful laptops or through the cloud, you can enrich your analysis with insights from machine learning models easily and instantly. Power BI provides integrated tools (closely related to Power BI Desktop and data flows) that allow you to use machine learning models developed by data scientists on Azure Machine Learning, models trained and deployed through Azure AutoML, or services exposed by Cognitive Services directly through a convenient graphical interface. The only drawback is that these tools (known as advanced AI) are only enabled if you use an Embedded capacity, Premium capacity, or Premium Per User (PPU) license. Does this mean that a user using Power BI Desktop or simply the Power BI service with a Pro license cannot benefit from machine learning? Absolutely not, and we'll show you how to do it thanks to Python and R.

In this chapter, you will cover...