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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

Using row groups/column groups

Row groups and column groups in paginated reports are essential features that provide a structured way to organize and present data. They play a crucial role in preparing and analyzing data for reporting.

Let’s explore how row groups and column groups help users in this process.

Organizing and structuring data

It’s important to understand why you should use row groups and column groups when creating reports in Power BI Report Builder. Let’s dive deeper into more information on why they are important and the use cases for them:

  • Row groups:
    • Importance:
      • Hierarchical structure: Row groups allow users to create a hierarchical structure in the report based on the values in a specific column. This is particularly useful for representing data in a nested or grouped manner.
      • Logical organization: By grouping rows based on certain criteria (for example, category and date range), users can logically organize data, making it easier...

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