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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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Toc

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

Questions

  1. What is the primary focus of managing relationships in Power BI?
    1. Writing efficient code
    2. Visualizing data
    3. Data modeling
    4. Advanced analytics
  2. Why is bidirectional cross-filtering (BDCF) considered a double-edged sword in Power BI?
    1. It is too complicated to implement
    2. It can enhance capabilities but may lead to errors and performance issues
    3. It is only suitable for small datasets
    4. It is a default setting for all relationships
  3. What is bidirectional cross-filtering, and how does it enhance data analysis in Power BI?
    1. A tool for data duplication
    2. A feature allowing tables to filter each other in both directions
    3. A method to create circular references
    4. A default setting for relationships
  4. Why is understanding cardinality crucial in Power BI data modeling?
    1. It is a technical detail without any impact
    2. It defines the nature of relationships between tables
    3. It only influences data visualization
    4. It is essential for writing efficient code
  5. What does one-to-one (1:1) cardinality mean in Power BI...
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