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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

Splitting columns

When working with data, particularly data extracted directly from source systems, there often comes a time when we will need to split columns to gain the desired dimensions for our analysis. This might be because the software or database of that source system might store that data in a particular format/encoding/arrangement. The most common example of this could be splitting a Date field in order to extract dimensions for [Day], [Month], and [Year].

In this example, we will connect and open the calendar.xlsx file. This Excel table includes one column of dates (as shown in Figure 4.8) and is to be used as a date table within Power BI. In this example, we might need to extract the individual date components for our analysis. Once connected, select Transform data to enter Power Query once again.

Figure 4.8 – The Date column within the date table in Power BI

Figure 4.8 – The Date column within the date table in Power BI

In order to split the columns, we will use the prebuilt function for splitting...

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