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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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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

Who’s responsible for cleaning data?

Businesses rely on data to inform strategies, make informed decisions, and gain a competitive edge. However, the process of ensuring data cleanliness is not automatic; it requires a well-defined strategy and a team of individuals with specific roles. In this section, we will explore the key roles responsible for cleaning data within a business and shed light on the importance of each position:

  • Data steward: At the forefront of data cleaning responsibilities is the data steward. This role involves overseeing the overall quality and integrity of data within the organization. Data stewards act as guardians of data, ensuring that it aligns with established standards and complies with regulations. They play a crucial role in developing and implementing data quality policies, monitoring data health, and addressing issues promptly.
  • Data analysts: They are instrumental in the hands-on work of cleaning and preparing data for analysis....

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