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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

Data Modeling and Managing Relationships

After learning about how to write efficient and performant code, we must now take the next step in preparing and cleaning data for our analytics. This chapter is dedicated to comprehensively understanding and managing data relationships within Power BI to ensure clean and reliable data for effective decision-making. It addresses the often-overlooked issue of dirty data arising from poorly designed data models.

For those confused about why data modeling is part of this book, it’s crucial to understand that without proper structuring and optimization of data, analysis and visualization in Power BI would be inefficient and unreliable. The desired Power BI semantic model often necessitates transformations to ensure data accuracy, consistency, and performance, thus emphasizing the indispensable role of data modeling in the process of data cleaning.

The chapter consists of the following topics:

  • Understanding the basics of data...
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