Does Creating a View table in Warehouse impact Performance when used in Semantic model

[Sreejisha]

I have created View in my Warehouse using SQL queries. When I used in a Semantic model. I am getting a Warning message. Is this a problem. ? Will it effect the Performance in my report?

[Sreejisha]

Thanks Everyone!

[suparnababu8]

Hi @Sreejisha 

The warning it self saying DAX queries in your sematic model may fall back to direct query, when you use SQL analytics endpoint items such as views. Fallback into dirtect query means, when the sematic model can't process the query efficently & direct query is not allowed in your report visulas.

So, workaround is refresh the sematic model to avoid issues, If possible use the materlized tables insted of views.

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[burakkaragoz · Accepted solution]

Hi @Sreejisha ,

Creating a view in the Warehouse generally doesn’t have a big performance impact by itself, since views are just saved SQL queries and don’t store data. But the real performance hit can come when those views are used in semantic models, especially if:

• The view includes complex joins or filters
• You're using Direct Lake mode, but the view forces a fallback to DirectQuery
• You're referencing the view multiple times in visuals or measures

If your view is just a simple SELECT * or has light filtering, the impact might be minimal. But once you start layering logic or chaining views, things can slow down—especially at scale.

One workaround folks use is creating composite models or duplicating logic in Power BI instead of relying too much on views. But I get that sometimes views are just more convenient or necessary.

Hope this helps a bit!

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[nilendraFabric]

Hi @Sreejisha 

when you add a view (as opposed to a base table) from your Warehouse to a semantic model, queries against that view will always fall back to DirectQuery mode, even if you are using Direct Lake for tables. This means that every time a report visual queries the view, it sends a live query to the underlying database rather than leveraging the high-speed in-memory analytics of Direct Lake.

Direct Lake (for tables): Offers the best performance because it loads only the necessary data into memory, enabling fast, interactive analytics.
• DirectQuery (for views): Is slower because each query must be executed live against the Warehouse, introducing latency and potential bottlenecks, especially with complex views or large datasets

The warning you see is accurate: using views in your semantic model can negatively impact report performance because queries against views always use DirectQuery mode, which is slower than Direct Lake. For best performance, use tables wherever possible, and only use views when absolutely necessary-keeping them as simple as possible