Forum Discussion
How to Use Dataflows Gen2 Without Creating a Lakehouse in Microsoft Fabric
- 5 months ago
Hi bdpr_95 ,
Thanks for the details.
Yes, you are correct Since deployment pipelines support only Dataflow Gen2, you will need to go with Gen2 for Dev to Prod movement. But in Gen2, the staging Lakehouse is required and we cannot avoid it at the moment. Even if you only want to use the data in a semantic model, Fabric will still create or use a Lakehouse in the backend. So in your case, the best way is to use Gen2, let it load data into a Lakehouse you can keep it just for staging purpose, and then connect your semantic model to it. As of now, there is no option to achieve Gen1-like behavior without storage in Gen2.Hope this helps. Let me know if you need anything else.
Regards,
Community Support Team.
Hi bdpr_95 ,
Thanks for the details.
Yes, you are correct Since deployment pipelines support only Dataflow Gen2, you will need to go with Gen2 for Dev to Prod movement. But in Gen2, the staging Lakehouse is required and we cannot avoid it at the moment. Even if you only want to use the data in a semantic model, Fabric will still create or use a Lakehouse in the backend. So in your case, the best way is to use Gen2, let it load data into a Lakehouse you can keep it just for staging purpose, and then connect your semantic model to it. As of now, there is no option to achieve Gen1-like behavior without storage in Gen2.
Hope this helps. Let me know if you need anything else.
Regards,
Community Support Team.
Hi bdpr_95,
I hope the information provided above assists you in resolving the issue. If you have any additional questions or concerns, please do not hesitate to contact us. We are here to support you and will be happy to help with any further assistance you may need.
Regards,
Community Support Team.
- v-hjannapu5 months agoCommunity Support
Hi bdpr_95,
I hope the above details help you fix the issue. If you still have any questions or need more help, feel free to reach out. We are always here to support you.
Regards,
Community Support Team.