Book Image

Data Cleaning with Power BI

By : Gus Frazer
Book Image

Data Cleaning with Power BI

By: Gus 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)
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

Assessing data relevance

Data is only valuable when it is relevant to the questions we seek to answer and the goals we want to achieve. Irrelevant or extraneous data can clutter reports and hinder the decision-making process.

Therefore, it is crucial to consider data relevance during the data import stage. In this section, we will emphasize the importance of evaluating data relevance and ensuring that only pertinent data is imported into Power BI. By filtering and transforming data thoughtfully, you will gain a deeper understanding of your business objectives and derive meaningful insights from their Power BI visualizations.

Power BI’s data transformation capabilities allow users to filter out irrelevant data during the import process. For example, when importing sales data, users can filter the data to include only the relevant product categories, time periods, or regions that align with the analysis objectives. Moreover, Power BI’s query editor provides a wide...