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I'm trying to find a definitive answer on the subject of support for composite models in Fabric. I've read that composite models are not supported, which I can understand if my dataset combines data from e.g. an existing Power BI dataset and an Excel file (think of a scenario where I want to enrich a central data model with some supplementary data in the form of departmental or regional budgets or forecasts).
However, if I have an existing Fabric semantic model (based on a Lakehouse/Warehouse) and I upload my Excel file to OneLake, can I create a new semantic model that combines data from both (as long as the resultant model is published to a Fabric workspace)?
Solved! Go to Solution.
From Power BI desktop, you can live connect to a semantic model created off of a lake house, and combine with other sources. However, queries to the semantic model (created off of the lakehouse), will fallback to DirectQuery (vs DirectLake).
From Power BI desktop, you can live connect to a semantic model created off of a lake house, and combine with other sources. However, queries to the semantic model (created off of the lakehouse), will fallback to DirectQuery (vs DirectLake).
Hi,
Please create it and test it you will know whether it will work for you or not.You can think about alternate approach incase if it have any issues.
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