Should the Datawarehouse be in Star or Snowflake for Powerbi Semantic model

[NewUser777]

I want to know if one wishes to build a Semantic Model for a Data Domain in Power BI premium then is it a must condition to have the Datawarehouse \ Datamart to be in Star or Snowflake schema ?

Example : 

Hr has one data domain say Learning in  star schema to serve the reporting requirements of learning in Hr department 

Also if one doesn't have the datawarehouse in star schema or snowflake schema then should one first build the star schema or snowflake schema on the warehouse and then pursue building semantic model for the data domain ? 
I understand that Semantic models in Powebi for large datasets must remain under some size but to get there I strongly believe the Semantic model should be built on already existing warehouse schema

.

[lbendlin]

The data model will be dictated by the business question you are trying to answer.  Ideally your datawarehouse or data lake does not mandate one or the other schema, but allows you as the developer to consume the objects and join them according to your users' needs.

[NewUser777]

@lbendlin Thanks , here is what I have found from Microsoft 

Semantic modeling is predominately used for read-heavy scenarios, such as analytics and business intelligence (OLAP), as opposed to more write-heavy transactional data processing (OLTP). This is mostly due to the nature of a typical semantic layer:

• Aggregation behaviors are set so that reporting tools display them properly.
• Business logic and calculations are defined.
• Time-oriented calculations are included.
• Data is often integrated from multiple sources.

Traditionally, the semantic layer is placed over a data warehouse for these reasons.

https://learn.microsoft.com/en-us/azure/architecture/data-guide/relational-data/online-analytical-pr...

So we do need a Datawarehouse layer for Power bi semantic model