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

Summary

In this chapter, you began your journey into the practical aspects of data cleaning within Power BI. You covered some of the most common data cleaning steps in Power BI, including removing duplicates, handling missing data, splitting columns, merging tables, dealing with date formats, replacing values, and creating calculated columns versus measures.

The chapter also highlighted the importance of replacing values in your data. Outliers, incorrect values, or inconsistent formats can hinder analysis. You learned about various scenarios where replacing values is necessary and used the Replace Values function in Power Query to fix errors and standardize data.

Lastly, the chapter explored the difference between calculated columns and measures in Power BI and explained when to use each option and their respective benefits. Calculated columns are best suited for row-level calculations, while measures are ideal for aggregations and calculations based on visual context. The chapter...

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