Cleaning Messy Data with Copilot

In this section, you focus on one of the most common real-world tasks in Excel: cleaning messy data.

Instead of working with clean examples, you deal with inconsistent, unstructured datasets that come from different sources.

What Messy Data Looks Like

Real datasets are often combined from multiple tools and people. Different formats, missing values, and inconsistent naming make the data hard to use.

Copilot helps you transform this data faster and with less manual work.

What You Will Learn in This Section

• You start by fixing the structure of the dataset. You standardize column names, identify missing values, and use Copilot to generate formulas that would normally take time to build;
• Next, you split and extract data from messy fields. You turn combined text into clean columns like first name, last name, department, and region;
• Then you fix inconsistent formats. You convert different representations of the same values into a single consistent format that Excel can work with;
• Finally, you remove duplicates in a controlled way. You keep your original data safe while creating a clean version of the dataset.