Data Cleaning with Power BI: The definitive guide to transforming dirty data into actionable insights

by Gus Frazer

Overview

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.

Product Details

ISBN-13:	9781805126058
Publisher:	Packt Publishing
Publication date:	02/29/2024
Sold by:	Barnes & Noble
Format:	eBook
Pages:	340
File size:	16 MB
Note:	This product may take a few minutes to download.

About the Author

Gus Frazer is a seasoned analytics consultant who focuses on business intelligence solutions. With over eight years of experience working for the two market-leading platforms, Power BI (Microsoft) and Tableau, he has amassed a wealth of knowledge and expertise. He also has experience in helping hundreds of customers to drive their digital and data transformations, scope data requirements, drive actionable insights, and most important of all, clean data ready for analysis.

Table of Contents

Table of Contents

1. Introduction to Power BI Data Cleaning
2. Understanding Data Quality and Why Data Cleaning is Important
3. Data Cleaning Fundamentals and Principles
4. The Most Common Data Cleaning Operations
5. Importing Data into Power BI
6. Cleaning Data with Query Editor
7. Transforming Data with the M Language
8. Using Data Profiling for Exploratory Data Analysis (EDA)
9. Advanced Data Cleaning Techniques
10. Creating Custom Functions in Power Query
11. M Query Optimization
12. Data Modeling and Managing Relationships
13. Preparing Data for Paginated Reporting
14. Automating Data Cleaning Tasks with Power Automate
15. Making Life Easier with OpenAI