Summary  
This chapter covers data cleaning and transformation techniques such as removing duplicates, filtering rows, renaming and changing data types, splitting and merging columns, unpivoting data, creating calculated columns, aggregating, and profiling to prepare data for analysis.

General domain of usage  
Business intelligence and reporting

In Power Query, **data cleaning** and **transformation** involve several key steps to prepare raw data for analysis. Initially, you import data from various sources such as Excel, databases, or web pages. The **cleaning** process includes removing duplicates, filtering rows, and correcting errors. **Transformation** steps involve renaming columns, changing data types, and merging or splitting columns to structure the data properly. 

**Advanced transformations** include unpivoting columns, creating calculated columns, and aggregating data. These actions help ensure the data is accurate, consistent, and ready for creating insightful visualizations and reports in Power BI.


What is the first step in preparing your data for cleaning in Power BI?

Power BI is an essential tool for any aspiring data analyst or business professional. Learn how to transform raw data into insightful visualizations and interactive dashboards, connect to various data sources, and create compelling reports for informed decision-making.

Dive into the world of Power BI and build a solid foundation. You'll cover everything from installation and setup to connecting data sources and creating your first report.

Explore essential data preparation techniques, including cleaning, transforming, and combining multiple data sources. You'll also tackle handling missing values, data profiling, and various data manipulation methods.


Master the fundamentals of data modeling, from understanding data models and creating relationships to getting the hang of DAX basics. You'll also learn to create measures and calculated columns.


Discover various visualization techniques and customize visuals for better insights. You'll also explore advanced features like slicers, filters, and drill-down/drill-through capabilities to enhance your data analysis.


Boost the usability and storytelling power of your reports by using themes, configuring report pages, and leveraging advanced features like the Analyze feature and identifying outliers. You'll also create groups, bins, and clusters for deeper insights.


Data Cleaning and Transformation

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Data Cleaning and Transformation