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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

Summary

In this chapter, we explored aspects of data quality assessment and preparation during the process of importing data into Power BI. The chapter began with an understanding of the significance of clean data and the need to address data quality concerns. It emphasized that the top three factors to consider are data completeness, accuracy, and consistency, as they lay the foundation for reliable analyses and visualizations.

You learned about using Power BI’s data profiling capabilities to assess data completeness. By visualizing missing values and identifying columns that demand attention, you gained the skills to ensure a thorough and complete dataset.

Moving forward, your exploration of data accuracy unfolded with Power BI’s versatile tools such as conditional formatting and data profiling. These tools empower you to validate accuracy, detect errors, and pinpoint outliers.

Delving into data consistency, Power BI’s strong data modeling capabilities...

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