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Return to [[Power_Query_–_Basic|Main Page]] | Return to [[Power_Query_–_Basic|Main Page]] | ||
→ Continue to [[Power Query – Importing Data|Module 2: Importing and Managing Data]] | → Continue to [[Power Query – Importing and Managing Data|Module 2: Importing and Managing Data]]. |
Revision as of 17:47, 18 June 2025
Module 1: Introduction to Power Query
What is Power Query?
Power Query is a data connection and transformation tool built into Microsoft Excel. It allows you to import, clean, reshape, and combine data from multiple sources.
You can find Power Query in Excel 2016 and later, under the Data tab in the section called Get & Transform Data.
Why Use Power Query?
- Automates repetitive data-cleaning tasks
- Simplifies combining data from various sources
- Eliminates the need for manual copy-pasting or complex formulas
- Keeps a full record of all applied steps for transparency and easy modification
Where to Find It
- 1. Open Microsoft Excel
- 2. Go to the Data tab
- 3. Locate the Get & Transform Data group
- 4. Click Get Data to begin importing
Hands-on Exercise
Goal: Open Power Query Editor and explore its interface.
File needed: Download Sales_January.xlsx
Steps:
- Open Excel and create a new blank workbook
- Go to the Data tab → Get Data → From File → From Workbook...
- Select the file Sales_January.xlsx and click Import
- In the Navigator window, select the worksheet and click Transform Data
- The Power Query Editor will open
- Review the following interface components:
- **Query Pane** (left): shows loaded queries (e.g., Sales_January)
- **Data Preview** (center): preview of your data table
- **Applied Steps** (right): list of transformations applied to the data
- **Ribbon Tabs**: Home, Transform, Add Column, View
Key Concepts
- Query: A set of steps used to load and transform data
- Applied Steps: Each operation is recorded and can be edited or deleted
- Load vs. Transform: You can either load data directly or open the editor to make changes first
Return to Main Page
→ Continue to Module 2: Importing and Managing Data.