Can I write a dataframe directly to an existing dataset/semantic model?

[poweruser1]

Is it possible to write a dataframe in a Fabric Notebook directly to a table in an existing Power BI dataset/semantic model that lives in the same workspace as the Notebook? I have the dataframe all set, i just dont know how to move it to my Power BI model.

[Cookistador · Accepted solution]

Hello @poweruser1 

the recommended and most integrated way to achieve this in Microsoft Fabric is by leveraging the Lakehouse.

Here's the typical workflow:

1. Write your DataFrame to a Lakehouse table (Delta table). This is the most efficient and integrated way to get data from your Fabric Notebook into a format that Power BI can easily consume within the same workspace.
2. Connect your Power BI dataset to this Lakehouse table. If your Power BI dataset is already in Direct Lake mode or set up to import from a Lakehouse, this process is seamless.

[v-menakakota]

Hi @poweruser1   ,
Thank you for reaching out to us on the Microsoft Fabric Community Forum.

I would also take a moment to thank  @burakkaragoz  and @Cookistador   , for actively participating in the community forum and for the solutions you’ve been sharing in the community forum. Your contributions make a real difference. 

The recommended way to move your DataFrame from a Fabric Notebook to a Power BI dataset is to write it to a Lakehouse Delta table in the same workspace. Then, connect your Power BI dataset to that table.

This method works best when using Direct Lake or import mode, and it ensures everything stays integrated within Fabric.

If this post was helpful, please give us Kudos and consider marking Accept as solution to assist other members in finding it more easily.
Best Regards, 
Menaka.
Community Support Team 

[v-menakakota]

Hi @poweruser1 ,

May I ask if you have resolved this issue? If so, please mark the helpful reply and accept it as the solution. This will be helpful for other community members who have similar problems to solve it faster. 

Thank you. 

[v-menakakota]

Hi @poweruser1 ,

I wanted to check if you had the opportunity to review the information provided. Please feel free to contact us if you have any further questions. If my response has addressed your query, please accept it as a solution so that other community members can find it easily. 

 
Thank you. 

[v-menakakota]

Hi  @poweruser1 ,

May I ask if you have resolved this issue? If so, please mark the helpful reply and accept it as the solution. This will be helpful for other community members who have similar problems to solve it faster. 

Thank you. 

[Cookistador · Accepted solution]

Hello @poweruser1 

the recommended and most integrated way to achieve this in Microsoft Fabric is by leveraging the Lakehouse.

Here's the typical workflow:

1. Write your DataFrame to a Lakehouse table (Delta table). This is the most efficient and integrated way to get data from your Fabric Notebook into a format that Power BI can easily consume within the same workspace.
2. Connect your Power BI dataset to this Lakehouse table. If your Power BI dataset is already in Direct Lake mode or set up to import from a Lakehouse, this process is seamless.

[burakkaragoz · Accepted solution]

Yeah this is the right approach. Writing the DataFrame to a Lakehouse Delta table and then connecting your Power BI dataset to it is the most seamless way, especially if you're using Direct Lake or import mode. Just make sure your Lakehouse and dataset are in the same workspace, and you're good to go.

If my response resolved your query, kindly mark it as the Accepted Solution to assist others. Additionally, I would be grateful for a 'Kudos' if you found my response helpful.