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

De-identifying data

PII, also called personal information or personal data, is any information relating to an identifiable person. There are two types of PII – direct and indirect. Examples of direct identifiers are your name, your address, a picture of you, or an Radio Frequency Identification (RFID) associated with you. Indirect identifiers, on the other hand, are all those pieces of information that don't explicitly refer to you as a person, but somehow make it easier to identify you. Examples of indirect identifiers are your license plate number, your bank account number, the link to your profile on a social network, or your place of work.

The practice of de-identifying data is to manipulate PPIs so that it is no longer possible to identify the person who generated them.

There are two options for handling direct and indirect personal identifiers – either you decide to destroy them completely, or you decide to keep them separated from the rest of the data...