Automating Data Cleanup & Analysis with Power Query in Excel

In this lesson, you’ll learn how to automate one of the most time-consuming parts of data analysis: collecting and cleaning raw data. Instead of manually fixing spreadsheets every time new data arrives, you’ll use Power Query in Microsoft Excel and Power BI to build a repeatable, no-code workflow that does the work for you.

Power Query allows you to pull data from multiple sources, such as Excel files, folders, databases, and even PDFs, and transform that data before it is loaded into Excel. In this lesson, you’ll follow a realistic business scenario where monthly sales data arrives in separate files. Instead of cleaning each file manually, you’ll learn how to connect Power Query to a folder so all files are automatically combined.

You’ll explore the Power Query Editor interface, including queries, applied steps, and data previews. Step by step, you’ll transform the data by removing unnecessary columns, filtering unwanted values, splitting combined fields, renaming headers, changing data types, and creating calculated columns such as profit and days to ship. Each transformation is recorded, allowing Power Query to replay the same steps every time the data refreshes.

Once your data is clean, you’ll load it back into Excel and use Pivot Tables and Pivot Charts to analyze trends such as profit by year. Finally, you’ll see how adding a new file to the source folder requires only one click, Refresh, to automatically apply all transformations.

By the end of this lesson, you’ll understand how Power Query helps you spend less time fixing data and more time analyzing it, making it an essential tool for analysts, operations teams, and anyone working with recurring data.