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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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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

The Most Common Data Cleaning Operations

Now that you’ve built a strong knowledge of data quality and the importance of assessing and documenting your data cleaning process, it’s time to roll your sleeves up and get stuck into some data.

In this chapter, you will be learning how to deal with the most common data cleaning steps within Power BI, as listed next. For each of these example topics, you will find a step-by-step walk-through on how to carry out these transformations yourself.

We will cover the following specific topics:

  • Removing duplicates
  • Removing missing data
  • Splitting columns
  • Merging columns
  • Replacing outliers
  • Creating calculated columns versus measures

By the end of the chapter, you will have built a strong base of foundational knowledge on how to tackle some of the most common and simplest transformations that we often see needing to be done when connecting to data in Power BI.

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