Forum Discussion
Impactful Individualpower bi report based on multiple semantic models
You can use more than one Power BI semantic model in a single report, but there are two different scenarios:
1. Same report with multiple models,
You can connect to Model A and Model B and use visuals from both in one PBIX. However, the models stay separate: you generally can’t relate tables across them, and slicers/filters from one model usually won’t filter visuals from the other model.
2. Truly combining models,
You may be able to use a composite model (DirectQuery for semantic models) to add a second model and create relationships/combined measures. This depends on tenant settings and can introduce limitations such as performance, restricted modeling features, and more sensitivity to changes in the upstream models.You will need permission to all underlying semantic models. If upstream models change (rename/remove fields), your report can break. Also, cross-model filtering and “single set of slicers” is not automatic unless you implement an integration approach.
If your end goal is a single, consistent reporting experience, the most reliable approach is usually to build a combined semantic model upstream and then build reports from that one model.
Super UserHey powerbiexpert22 ,
Yes, you can create a Power BI report that uses or combines two or more Power BI semantic models as a source, but not in the traditional way of simply merging them like tables in Power Query. Power BI does not allow you to use multiple live connections in a single report.
However, you can combine multiple semantic models by using a composite model with DirectQuery for Power BI datasets. In this approach, you connect to one semantic model first, then add another Power BI semantic model as an additional source. Power BI converts the report into a composite model, allowing you to create relationships between tables from different models and build measures across them.
That said, there are some limitations, such as performance dependencies on both models and restrictions on relationship types (typically many-to-one). For long-term scalability and cleaner architecture, many organizations prefer creating a new centralized semantic model that integrates all required data sources and then building reports on top of that single model.
In summary, while you cannot directly merge multiple published semantic models through multiple live connections, you can combine them using composite models, which is the most practical supported approach.
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Thanks for being part of the discussion !!!
Hi, can you explain more on the part 'performance dependencies on both models ' aspect of direct query connection to 2 semantic models.
