Guidance Needed: Creating Power BI Dataset Model Using REST API with Microsoft Fabric Real-Time Inte

[Mestu_Paul]

Hello Power BI community,

I'm currently working on a project that involves creating Power BI semantic models (datasets) using the Power BI REST API. Recently, I've encountered an issue: it seems that the traditional method of creating new dataset models via the REST API is no longer viable. The current guidance suggests leveraging Microsoft Fabric Real-Time Intelligence, and I've also come across references to using a Lakehouse as an alternative.

However, I'm struggling to find comprehensive documentation or a clear process to transition from creating tables (e.g., using endpoints like Create Lakehouse, Upload File, and Create Table) to building a Power BI dataset model.

Has anyone successfully implemented this workflow or found resources detailing how to create a Power BI dataset model after setting up tables in a Lakehouse using REST APIs? Any guidance, examples, or links to relevant documentation would be greatly appreciated.

Thank you in advance for your help!

[Mestu_Paul]

hi rajendraongole1 , thanks for your guidence, but I need rest api support instead of UI. Suppose I've a report already with some sample data, then i push the report in cloud. Now i want to create new semantic model using some table from lakehouse tables  using rest api and rebind it with pushed report (i can rebind via rest api).

Here I find how to create semantic model via rest api, but it is workspace specific not lakehouse. And I can not understand of its parts of request body. Like 
{

"path": "model.bim",

"payload": "ew0KICAiY29tcGF0a..GVzIjogWyBdDQogIH0NCn0=",

"payloadType": "InlineBase64"

}

[rajendraongole1]

Hi @Mestu_Paul - Start by creating tables in the Lakehouse through Fabric’s REST API endpoints. Use endpoints such as Create Lakehouse, Upload File, and Create Table to ingest your data into the Lakehouse. Once tables are created, you can directly query this Lakehouse data from Power BI.

Build Power BI Models with Direct Query: Power BI’s direct query mode supports both Lakehouse and Eventhouse tables within Fabric. After creating your tables in the Lakehouse, use Power BI Desktop to connect via direct query, which enables real-time reporting on Lakehouse data. This setup allows you to skip creating intermediate datasets entirely since Power BI can now query the Lakehouse directly.

For real-time updates, the Microsoft Fabric Real-Time Intelligence Suite provides tools like Eventstream and Eventhouse. These tools support direct data ingestion, transformation, and streaming to destinations, including the Lakehouse. Using Eventstream in combination with Power BI’s automatic page refresh, you can achieve near-instantaneous data visualization updates.

Please find the below reference links for more details and process flow:

Direct Lake mode and Power BI reporting - Microsoft Fabric | Microsoft Learn

Default Power BI semantic models - Microsoft Fabric | Microsoft Learn

Connecting Power BI to Fabric Lakehouse

Simplifying Migration to Fabric Real-Time Intelligence for Power BI Real Time Reports | Microsoft Co...