Book Image

Data Cleaning with Power BI

By : Gus Frazer
Book Image

Data Cleaning with Power BI

By: Gus Frazer

Overview of this book

Microsoft Power BI offers a range of powerful data cleaning and preparation options through tools such as DAX, Power Query, and the M language. However, despite its user-friendly interface, mastering it can be challenging. Whether you're a seasoned analyst or a novice exploring the potential of Power BI, this comprehensive guide equips you with techniques to transform raw data into a reliable foundation for insightful analysis and visualization. This book serves as a comprehensive guide to data cleaning, starting with data quality, common data challenges, and best practices for handling data. You’ll learn how to import and clean data with Query Editor and transform data using the M query language. As you advance, you’ll explore Power BI’s data modeling capabilities for efficient cleaning and establishing relationships. Later chapters cover best practices for using Power Automate for data cleaning and task automation. Finally, you’ll discover how OpenAI and ChatGPT can make data cleaning in Power BI easier. By the end of the book, you will have a comprehensive understanding of data cleaning concepts, techniques, and how to use Power BI and its tools for effective data preparation.
Table of Contents (23 chapters)
Free Chapter
1
Part 1 – Introduction and Fundamentals
6
Part 2 – Data Import and Query Editor
11
Part 3 – Advanced Data Cleaning and Optimizations
16
Part 4 – Paginated Reports, Automations, and OpenAI

Using ML to clean data

In addition to being a market-leading visualization platform, Power BI offers a suite of built-in machine learning features that empower users to take their data analysis and preparation to the next level. In this section, we will explore those features within Power BI and understand how they can be harnessed to streamline data cleaning, preparation, and enhancement.

Data cleaning with anomaly detection

Data cleaning is often the first step in the data preparation process. Anomalies or outliers in the data can skew analysis results and compromise the quality of reports. Power BI’s built-in anomaly detection feature can automatically identify and flag data points that deviate significantly from the norm. Power BI’s anomaly detection leverages machine learning algorithms to detect data points that are statistically different from the rest. Users can set the sensitivity level to control the number of anomalies detected.

Here are some examples...