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Data Cleaning with Power BI

Data Cleaning with Power BI

By : Frazer
5 (7)
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Data Cleaning with Power BI

Data Cleaning with Power BI

5 (7)
By: Frazer

Overview of this book

Microsoft Power BI offers a range of powerful data cleaning and preparation options through tools such as DAX, Power Query, and the M language. However, despite its user-friendly interface, mastering it can be challenging. Whether you're a seasoned analyst or a novice exploring the potential of Power BI, this comprehensive guide equips you with techniques to transform raw data into a reliable foundation for insightful analysis and visualization. This book serves as a comprehensive guide to data cleaning, starting with data quality, common data challenges, and best practices for handling data. You’ll learn how to import and clean data with Query Editor and transform data using the M query language. As you advance, you’ll explore Power BI’s data modeling capabilities for efficient cleaning and establishing relationships. Later chapters cover best practices for using Power Automate for data cleaning and task automation. Finally, you’ll discover how OpenAI and ChatGPT can make data cleaning in Power BI easier. By the end of the book, you will have a comprehensive understanding of data cleaning concepts, techniques, and how to use Power BI and its tools for effective data preparation.
Table of Contents (23 chapters)
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Free Chapter
1
Part 1 – Introduction and Fundamentals
6
Part 2 – Data Import and Query Editor
11
Part 3 – Advanced Data Cleaning and Optimizations
16
Part 4 – Paginated Reports, Automations, and OpenAI

Questions

  1. What percentage of time is generally spent on data cleaning and preparation in a data visualization project?
    1. 20-30%
    2. 50-80%
    3. 10-20%
    4. 80-100%
  2. Name three tools provided by Power BI for data preparation.
    1. Power Extract, data integration, data expressions
    2. Power Query, data modeling, SQL queries
    3. Data analytics, Query Editor, data mining
    4. Power Query, data modeling, DAX formulas
  3. What is the primary function of Power Query in Power BI?
    1. Creating visualizations
    2. Writing SQL queries
    3. Data transformation and preparation
    4. Building relationships between tables
  4. What is DAX, and how is it used in Power BI?
    1. As a data visualization tool
    2. As a programming language
    3. As a formula language for creating calculations and measures
    4. As a data storage format
  5. Why was DAX created, and what problem did it aim to solve?
    1. To create charts and graphs
    2. To bridge the gap between relational databases and spreadsheet tools
    3. To replace SQL queries
    4. To handle big data efficiently
  6. Explain the dual role of DAX as a formula...

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