- The default semantic model takes up unnecessary real estate in the Fabric workspace. If I don't want the default semantic model, I should be able to remove it.
- The default semantic model is confusing, because you cannot modify it through the default semantic model item, instead you need to look inside the SQL Analytics Endpoint to modify the default semantic model.
- The default semantic model doesn't support server timings and some other features in DAX studio. For this, you need to create a new custom semantic model.
- The default semantic model cannot be manually refreshed, so you cannot clear it's cache for performance testing. For this, you need to create a new custom semantic model.
Bottom line: the default semantic model is annoying and should be removed.
9 Comments
- fbcideas_migusrNew Member
Agreed ... this consumes un-necessary resources and is contributing to global warming. And that is a bad thing. Don't do bad things Microsoft! :)
- fbcideas_migusrNew Member
Thanks for posting this. I don't like the default semantic model either. We never use it. We create a new one every time from the lakehouse. I wish they would remove the L shape grouping with the default semantic model and SQL Analytics endpoint as well. It takes up too much real-estate and dirties up an otherwise beautiful organization of items. There are other ways to get to the SQL analytics endpoint. I say get rid of the L shape grouping and access the SQL analytics endpoint through the ... "more options". Or it isn't unreasonable to just access the SQL analytics endpoint using the toggle dropdown in the upper right corner of the lakehouse. Many of us are using SSMS anyway.
Or allow users to configure the L grouping option on or off. To us it is very annoying to have many lakehouses in a workspace and it take up this much space.
- Thomas_EvansNew Member
Thanks for posting! Microsoft, please get rid of this unnecessary use of resources.
- CWright2New Member
Microsoft, please get rid of this unnecessary use of resources
- AFraaijNew Member
Also using a notebook to create a Lakehouse based on import sempy.fabric as fabric
It creates default semantic models outside the normal structure of Lakehouse creation like
--- LakehouseName
----- SemanticModelName
Example:
--- Lakehouse1
---- Lakehouse1
When you now delete the Lakehouse also the default semantic model is deleted.
To somekind of reason the sempy.fabric.create_lakehouse does create the default Semanticmodel not in this structure and when deleting the Lakehouse the semanticmodel still exists.
Needing to delete the workspace to remove it.
No issue for development but can not be done in production workspaces.
With sempy.fabric it also was possible to end with multiple semanticmodels having the same name, seeing in my development workspace:
Lakehouse3
Lakehouse3
Lakehouse3
- fbcideas_migusrNew MemberStatus added:New
- ToddChittSuper UserTotally agree. Plus the "SQL Analytic Endpoint" for every Warehouse and Lakehouse is exactly the same, so why do we need to have it listed multiple times under multiple Lakehouses? (Department of Redundancy Department)
- 42cdxNew MemberTotally agree
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