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Data Cleaning with Power BI

You're reading from  Data Cleaning with Power BI

Product type Book
Published in Feb 2024
Publisher Packt
ISBN-13 9781805126409
Pages 340 pages
Edition 1st Edition
Languages
Author (1):
Gus Frazer Gus Frazer
Profile icon Gus Frazer

Table of Contents (23) Chapters

Preface 1. Part 1 – Introduction and Fundamentals
2. Chapter 1: Introduction to Power BI Data Cleaning 3. Chapter 2: Understanding Data Quality and Why Data Cleaning is Important 4. Chapter 3: Data Cleaning Fundamentals and Principles 5. Chapter 4: The Most Common Data Cleaning Operations 6. Part 2 – Data Import and Query Editor
7. Chapter 5: Importing Data into Power BI 8. Chapter 6: Cleaning Data with Query Editor 9. Chapter 7: Transforming Data with the M Language 10. Chapter 8: Using Data Profiling for Exploratory Data Analysis (EDA) 11. Part 3 – Advanced Data Cleaning and Optimizations
12. Chapter 9: Advanced Data Cleaning Techniques 13. Chapter 10: Creating Custom Functions in Power Query 14. Chapter 11: M Query Optimization 15. Chapter 12: Data Modeling and Managing Relationships 16. Part 4 – Paginated Reports, Automations, and OpenAI
17. Chapter 13: Preparing Data for Paginated Reporting 18. Chapter 14: Automating Data Cleaning Tasks with Power Automate 19. Chapter 15: Making Life Easier with OpenAI 20. Assessments 21. Index 22. Other Books You May Enjoy

Replacing values

When connecting to and analyzing data, there are often times when we might find outliers within the data. If we identify that there are values skewing the data or showing incorrectly, it’s important for us to be able to replace the data with the correct values.

There are many scenarios where you might need to do this in Power BI. Here are just some example scenarios:

  • Replacing variations of N/A or Not Applicable with a consistent value such as Unknown.
  • You may need to rename or reclassify certain values in your dataset to align with your reporting needs or to create meaningful categories. For instance, you can replace abbreviations or acronyms with their full names or group similar values together.
  • You can replace numeric code with descriptive labels or convert coded values into meaningful text representations.
  • In cases where your data contains missing or null values, you can use the Replace Values function to replace them with a specific...
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