Power Query Essentials: Combining and Restructuring Data

This course includes downloadable course instructor files and exercise files to work with and follow along.

Power Query Essentials: Combining and Restructuring Data teaches you how to reshape messy, scattered data into tables that are ready for real analysis. This course gives you a practical toolkit for cleaning and combining information before it reaches Excel or Power BI, so your reports stay accurate as your data grows. Many spreadsheets look tidy but hide structural problems. Quarterly figures split across columns, sales files scattered across regions, and duplicate records buried in separate systems all block simple tasks like charting trends or filtering by a single category. The course starts by naming these problems, so you know exactly what to fix and why it matters.

From there, you learn how to build core Power Query skills. Appending stacks of similar tables into one, while merging joins related tables to add new context. Conditional columns apply if-then logic without formulas, grouping pre-summarises data like a built-in pivot table, and unpivoting turns wide tables into a long, structured format. These skills come to life in real situations. You combine monthly sales files into a single report, merge transaction data with customer details, flag inventory as reorderable or healthy, and reconcile two systems to catch missing or changed records.

By the end, you will know how to clean, reshape, and combine data with confidence, then load it into a report that refreshes automatically. This course is suitable for analysts, Excel users, and anyone who works with data from multiple sources.

What You'll Learn:

• Stack rows from multiple data sources with append.

• Consolidate files from a folder into one table.

• Join customer details to sales transactions using merge.

• Identify matching and unmatched rows with merge joins.

• Convert column headers into row values using unpivot.

• Transform awkward reporting layouts into clean datasets.

• Create new categories based on specific data conditions.

• Flag records as 'valid' or 'invalid' with custom rules.

• Summarize data by single or multiple grouping fields.

• Calculate totals and counts before loading raw data.

• Compare two datasets to find missing or changed values.

• Design a repeatable workflow for ongoing data updates.

This course includes:

1. 48 minutes of video tutorials

2. 8 individual video lectures

3. Course and Exercise Files to follow along

4. Certificate of completion