ETL with Power Query: Import, Transform, and Load Data Efficiently

What is ETL?
ETL stands for Extract, Transform, Load — a process used to gather data from various sources, clean and shape it, and load it into a target system like a data warehouse or a Power BI data model.
ETL in Power BI with Power Query
Power BI performs ETL operations using Power Query Editor, which is a built-in tool for data preparation.
1. Extract (E)
Get Data
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You pull data from various sources like Excel, SQL Server, SharePoint, Web APIs, Azure, etc.
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In Power BI: Click Home > Get Data to import your data.
2. Transform (T)
Clean and Shape Data
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This is the core strength of Power Query.
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You can:
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Filter rows (e.g., remove nulls)
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Rename columns
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Merge or split columns
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Change data types
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Unpivot or pivot data
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Remove duplicates
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Create custom columns using M code
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Every action becomes a step in the query, which is repeatable and refreshable.
3. Load (L)
Push Data to Power BI Model
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After transformation, load the clean data into Power BI’s data model.
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This data is now ready for creating visuals, measures, and reports.
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You can also load it to Power BI Dataflows if building centralized models.
Example:
Suppose you have messy Excel files from five departments. Using Power Query, you can:
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Extract all files from a folder,
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Merge them into a single table,
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Remove duplicates and correct date formats,
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Then load the cleaned dataset into Power BI for dashboarding.
Key Benefits of ETL in Power Query:
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No need for external ETL tools for many cases.
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Visual interface, no-code/low-code.
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Reusable and refreshable queries.
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Seamless integration with Power BI.
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