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AshwiniPulipat
Frequent Visitor

Semantic model to composite model

Hello,

I have an semantic model which is used to generate various reports using that. Due to this we are facing schedule refresh error as data is exceeding it's limit. So we are trying to create composite model from the semantic data model which have parent to child relationship between them and we are going to use these composite model for scheduling data refreshes and for report generation we will be using semantic model. Is this work like this. I am new to this concept.can anyone help me in understanding the logic and whether this works or not and if not how to solve the issue. Thanks

1 ACCEPTED SOLUTION
VahidDM
Super User
Super User

Hi @AshwiniPulipat 

 

Creating composite models with parent-child relationships may not fully resolve your scheduled refresh errors caused by exceeding data size limits; instead, it's more effective to implement incremental refresh to handle large datasets efficiently, optimize your data model by removing unnecessary data, and consider upgrading to Power BI Premium or Premium Per User licenses for increased capacity and advanced features—these strategies are more likely to solve your issue and improve performance.

 

If this post helps, please consider accepting it as the solution to help the other members find it more quickly.

Appreciate your Kudos!! 

 

LinkedIn|Twitter|Blog |YouTube 

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1 REPLY 1
VahidDM
Super User
Super User

Hi @AshwiniPulipat 

 

Creating composite models with parent-child relationships may not fully resolve your scheduled refresh errors caused by exceeding data size limits; instead, it's more effective to implement incremental refresh to handle large datasets efficiently, optimize your data model by removing unnecessary data, and consider upgrading to Power BI Premium or Premium Per User licenses for increased capacity and advanced features—these strategies are more likely to solve your issue and improve performance.

 

If this post helps, please consider accepting it as the solution to help the other members find it more quickly.

Appreciate your Kudos!! 

 

LinkedIn|Twitter|Blog |YouTube 

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