Forum Discussion
Shared Semantic Models
the number of reports sharing the same model is not a problem per se.
We have dozens of report sharing the same Model on multiple customers' scenarios.
As GilbertQ said you must follow best practice when you design it:
- star-schema
- import mode preferred
- import only needed data (3 milion rows is not a big deal, 56 columns... do you really need of all them?)
- use correct data types
- pay attention to DAX you write in measures
- do not put too much visual in the same page because each of them will rise a query against the model (or use visuals that optimize this like multiple-row card instead of 50 cards for example)
- etc...
Hi bdpr_95
I have built shared semantic models for multiple customers and never experienced any performance issues. The only reason performance issues can come in is if potentially the model is not created in a star schema. Best practices haven't been done and the DAX isn't fully optimized, but could potentially be that the slowness is due to some performance issues on the semantic model.
Hi GilbertQ,
Thank you very much for the information. I'm considering using a semantic model to develop five different reports, and I wanted to understand whether I might face any performance issues in terms of interactivity.
In terms of the data model, we're using a star schema: one calendar table, one currency table, and a fact table. The fact table has around 3 million rows and 56 columns.
Do you think I could run into any problems?
the number of reports sharing the same model is not a problem per se.
We have dozens of report sharing the same Model on multiple customers' scenarios.
As GilbertQ said you must follow best practice when you design it:
- star-schema
- import mode preferred
- import only needed data (3 milion rows is not a big deal, 56 columns... do you really need of all them?)
- use correct data types
- pay attention to DAX you write in measures
- do not put too much visual in the same page because each of them will rise a query against the model (or use visuals that optimize this like multiple-row card instead of 50 cards for example)
- etc...