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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

Best practices with Power Automate

Some of the best practices to be aware of for data cleaning in Power Automate:

  • Workflow planning: Before diving into automation, carefully plan your data cleaning workflow. Identify the key steps that require automation and the triggers that will initiate the processes.
  • Error handling: Implement robust error-handling mechanisms within your automated workflows. This includes adding notifications for failed processes, enabling quick identification, and resolving issues. One example would be to check the flow checker from within your flow. To do this, select Flow check in the top right corner of the Power Automate toolbar.
  • Flow check will then provide details of any errors or warnings identified within your flow.
  • Testing and validation: Thoroughly test your automated data cleaning workflows in different scenarios. Validate the results to ensure that the automated processes align with your data quality standards.
  • Security considerations...

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