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npvinhloc108
New Member

Azure AS and TMDL deployment

Hi everyone,

We have a Azure AS to serve all our Power BI reports.

Currently we use the .bim file to deploy the model to Azure AS.

 

The file is getting bigger and becoming hard to maintain/control. We're thinking of changing it to TMDL (Tabular Model Definition Language (TMDL) | Microsoft Learn)

 

Has anyone deployed the TMDL to Azure AS using Powershell before?

 

--

Thank you.

2 REPLIES 2
v-rzhou-msft
Community Support
Community Support

Hi @npvinhloc108 ,

 

Do you mean that you try to export data with TOM Tool and manage these data in Azure Analysis Service?
As far as I know, the data may be something wrong due to export and load again and again from different applications. So I think this is not a good way.
I suggest you to try other features in Fabric like Data Factory or Data Engineering in Synapse.
You can create dataflows to connect to your data source or load your data into a lakehouse. You can also deploy a data pipline to monitor your data.
Microsoft Fabric Lakehouse is a data architecture platform for storing, managing, and analyzing structured and unstructured data in a single location. It's a flexible and scalable solution that allows organizations to handle large volumes of data using various tools and frameworks to process and analyze that data.

For reference:

What is Microsoft Fabric - Microsoft Fabric | Microsoft Learn

What is a lakehouse? - Microsoft Fabric | Microsoft Learn

 

Best Regards,
Rico Zhou

 

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

Hi @v-rzhou-msft 

 

What I'm trying to do is:

  • Create a script that could deploy the metadata only to Azure AS
  • .bim is a single file, so it's very easy to be conflict when multiple developers working on the same model at the same time (even when they are working in different measures/tables...)
    • I'm thinking of changing the .bim to folder of .TMDL files, so that we can use source control more effectively.

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