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Data Cleaning with Power BI

You're reading from   Data Cleaning with Power BI The definitive guide to transforming dirty data into actionable insights

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Product type Paperback
Published in Feb 2024
Publisher
ISBN-13 9781805126409
Length 340 pages
Edition 1st Edition
Languages
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Author (1):
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Gus Frazer Gus Frazer
Author Profile Icon Gus Frazer
Gus Frazer
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Table of Contents (23) Chapters Close

Preface 1. Part 1 – Introduction and Fundamentals FREE CHAPTER
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

Importing Data into Power BI

Now that we understand the importance of cleaning data and even how to tackle some of the most common data-cleaning operations, it’s time to start bringing some data into Power BI.

When it comes to importing data into Power BI, there are six main topics, as listed next, to consider. Most importantly, for the top three, there are metrics that help us identify how clean data is prior to us working on it. In this chapter, you will learn about these topics and how you can use the Power BI platform to assess these metrics within your own data.

Specifically, we will be going through the following topics:

  • Understanding data completeness
  • Understanding data accuracy
  • Understanding data consistency
  • Assessing data relevance
  • Assessing data formatting
  • Assessing data normalization, denormalization, and star schemas

By the end of this chapter, you will be able to confidently assess how clean the data you’ve imported...

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