Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Data Cleaning with Power BI
  • Table Of Contents Toc
  • Feedback & Rating feedback
Data Cleaning with Power BI

Data Cleaning with Power BI

By : Frazer
5 (7)
close
close
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)
close
close
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 is the primary purpose of EDA?
    1. To finalize the dataset
    2. To summarize data characteristics and gain insights
    3. To create predictive models
    4. To validate machine learning algorithms
  2. What are the benefits of conducting well-carried-out EDA when connecting to data?
    1. Identifying potential outliers
    2. Ignoring data quality issues
    3. Skipping data visualization
    4. Avoiding modeling choices
  3. Which of the following is NOT a fundamental data profiling capability offered by Power BI?
    1. Column Quality Assessment
    2. Column Distribution Analysis
    3. Column Transformation
    4. Column Profile Views
  4. How can you access the data profile views in Power BI?
    1. From the Home tab
    2. Within Power Query, open the View tab
    3. Using the Visualization pane
    4. Through Power BI Dashboard settings
  5. What does the Column distribution view in Power BI provide?
    1. Assessment of data quality
    2. Histograms and statistics
    3. Data completeness percentage
    4. Visualization of column names
  6. What does the Column quality view in Power BI assess, and how is it...

Unlock full access

Continue reading for free

A Packt free trial gives you instant online access to our library of over 7000 practical eBooks and videos, constantly updated with the latest in tech
bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY