Append vs. Merge in Power BI

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1. Purpose:

• Append:Primary Use: Combine rows from two or more tables into a single table. This operation is similar to a SQL UNION.Ideal For: When you have data tables with the same structure (same columns) and you want to stack them on top of each other.
• Merge:Primary Use: Combine columns from two or more tables based on a related key or common column. This operation is similar to a SQL JOIN.Ideal For: When you need to bring together related data from different tables into a single table based on a shared key.

2. Data Structure Requirements:

• Append:Data Structure: Tables must have the same column structure (same column names and data types) to append successfully.Result: Creates a new table that combines rows from the original tables, expanding vertically.
• Merge:Data Structure: Tables must have a common column (key) that links them together.Result: Creates a new table that combines columns from the original tables, expanding horizontally, with options for different types of joins (Inner, Outer, Left, Right, etc.).

3. Use Cases:

• Append:Common Scenarios: Combining data from multiple regions, months, or years into a single table for analysis.Example: You have sales data for different months in separate tables, and you want to create a single table that includes all sales data across the months.
• Merge:Common Scenarios: Enriching a fact table with additional details from a lookup table.Example: You have a sales transaction table and a customer details table. You want to merge them to create a single table that includes both the transaction details and the customer information.

4. Performance Considerations:

• Append:Performance: Generally faster and less resource-intensive than merge, especially if the tables have the same structure and are not excessively large.Impact: Can increase the size of your data model if not managed carefully, as it essentially duplicates the data from the original tables.
• Merge:Performance: Can be more resource-intensive, especially with large tables or complex joins. It's important to ensure that the keys used for merging are optimized and that unnecessary columns are removed.Impact: Merging large tables or using complex join conditions can slow down your queries and report refresh times.

5. When to Use:

• Append:When: Use append when you have multiple datasets with the same structure that you want to combine into one.Example: Combining survey results from different departments into a single table.
• Merge:When: Use merge when you need to combine related data from different tables, especially when you want to enrich a dataset with additional information.Example: Merging a product sales table with a product details table to include product names and categories in your sales analysis.

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