March 31 - April 2, 2025, in Las Vegas, Nevada. Use code MSCUST for a $150 discount! Early bird discount ends December 31.
Register NowBe one of the first to start using Fabric Databases. View on-demand sessions with database experts and the Microsoft product team to learn just how easy it is to get started. Watch now
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.
March 31 - April 2, 2025, in Las Vegas, Nevada. Use code MSCUST for a $150 discount!
Your insights matter. That’s why we created a quick survey to learn about your experience finding answers to technical questions.
Arun Ulag shares exciting details about the Microsoft Fabric Conference 2025, which will be held in Las Vegas, NV.
User | Count |
---|---|
39 | |
22 | |
21 | |
10 | |
10 |
User | Count |
---|---|
60 | |
56 | |
22 | |
14 | |
12 |