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)
Section 1: Best Practices for Using R and Python in Power BI
Section 2: Data Ingestion and Transformation with R and Python in Power BI
Section 3: Data Enrichment with R and Python in Power BI
Section 3: Data Visualization with R in Power BI

Extracting values from text using regex in Power BI

The last use case we want to present happens very often when dealing with shipments of goods to customers. Sometimes, it happens that a fraudster manages to steal the goods addressed to a customer; therefore, the customer must be refunded by the company. The defrauded customer then contacts Customer Care to request a refund. If the management system provided to the Customer Care operator who has to manage the case does not allow you to enter the information of the refund in a structured way, the operator must resort to the only possible method: the entry of a free text note associated with the order, which specifies the amount, the reason and the date of the refund.

You already know that information entered in free text is every analyst's nightmare, especially when your boss asks you to analyze the very information entered in these infamous notes.

In the repository that comes with this book, you can find the OrderNotes...