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Can someone explain this. What do you mean by table expansion happens with the table is created.
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Hi, @Cyriackpazhe
In Power BI, table expansion refers to the process by which a table dynamically adjusts to include additional columns or rows on top of certain operations or relationships.
When you use DAX (Data Analysis Expression) in Power BI, table expansion happens during the evaluation of the measure. The DAX engine creates a virtual table that contains columns from the related table. This allows for more comprehensive filtering and grouping. For example, if you have a sales table associated with a customer table, the expanded version of the sales table will include columns from the customers table. This helps apply filtering and aggregation across related tables. You can check the following link:
DAX - Table Expansion Explained | Burningsuit
In Power BI reports, you can create tables that dynamically scale based on user interactions, such as slicer selection. For example, you might have a slicer that allows users to select the columns they want to see in a table.
When a user selects different columns through the slicer, the table dynamically adjusts to show all the values for those selected columns. You can check the following link:
Solved: Dynamically Expanding Table in Power BI Based on S... - Microsoft Fabric Community
How to Get Your Question Answered Quickly
Best Regards
Yongkang Hua
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Hi, @Cyriackpazhe
In Power BI, table expansion refers to the process by which a table dynamically adjusts to include additional columns or rows on top of certain operations or relationships.
When you use DAX (Data Analysis Expression) in Power BI, table expansion happens during the evaluation of the measure. The DAX engine creates a virtual table that contains columns from the related table. This allows for more comprehensive filtering and grouping. For example, if you have a sales table associated with a customer table, the expanded version of the sales table will include columns from the customers table. This helps apply filtering and aggregation across related tables. You can check the following link:
DAX - Table Expansion Explained | Burningsuit
In Power BI reports, you can create tables that dynamically scale based on user interactions, such as slicer selection. For example, you might have a slicer that allows users to select the columns they want to see in a table.
When a user selects different columns through the slicer, the table dynamically adjusts to show all the values for those selected columns. You can check the following link:
Solved: Dynamically Expanding Table in Power BI Based on S... - Microsoft Fabric Community
How to Get Your Question Answered Quickly
Best Regards
Yongkang Hua
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
If you observe, the result of SalesA and SalesB variables is a table and not a scalar value. When SalesA is defined, it considers Sales{Date] <- Date[Date] as active relationship and table expansion happens accordingly. Similarly, for SalesB active relationship would be Sales[DueDate] <- Date[Date].
Expanded of version of SalesA and SalesB tables contains all the columns of Sales table and Date table, However the mapping of date columns would be as per the relationship that is active at the time when the table variables are defined.
SalesA - Sales{Date]
SalesB - Sales[DueDate]
This is the reason when you use RELATED function by iterating over SalesB, the corresponding month value would be as per DueDate but it would not be as per the Date.
Hope this answers your question.
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