XMLA edited and Large Semantic model properties

[R1k91]

We are planning a large-scale migration for a customer from one region to another.

The most complex semantic models involved are:

• Models with incremental refresh enabled
• Models modified using XMLA
• Large semantic models

Before proceeding, we are compiling a list of these models using a script (ideally with consistent language/technique across all).

So far, we have identified the models with incremental refresh using SemPy and Semantic-LinkLabs.

However, we are struggling to identify models that have been modified using XMLA or that qualify as large semantic models.

It seems the TOM library does not provide a direct option for this. The only solution we’ve found is a PowerShell cmdlet, which provides the StorageMode property (values: abf or PremiumFiles).

Reference: Power BI Premium Large Models Documentation.

Does anyone know how to identify whether a model is large and/or uses incremental refresh via the TOM library?

Alternatively, is there any other reliable method to achieve this?

[SaiTejaTalasila]

Hi @R1k91 ,

You create a power shell script using the below rest API and you can pull json response and you can find the partition details from that you identify whether it is incremental refresh one or not.GET https://api.powerbi.com/v1.0/myorg/groups/{groupId}/datasets/{datasetId}

You can keep your workspace id and dataset id in one excel table and you can pass those values to API endpoint and get the response to new column and you can analyse that data.

I hope it will be helpful.

Thanks,

Sai Teja 

[R1k91]

Thank you for the answer.
As stated in the question the incremental refresh is not an issue. Sempy and Semantic Link Labs already gave us that results. The problem is to know if a model is modified in XMLA or Large Semantic Model.