Unable to change update method to replace in dataflow

[IAMCS]

task : suppose we have a task to ingest some tables from one warehouse to a new warehouse in fabric using dataflow.

process: it can be done by creating a new dataflow as item at workspace level or first we can create the new warehouse and within that warehouse we can create the dataflow.

problem: while creating the dataflow from within the warehouse,
I dont see any window where we can do coulmn mapping and change update method to "append"

but if we create the dataflow not from within warehouse but at workspace levell as new item we get this window where we can do column mapping and choose update method to append or replace.


why I am sticking to 1st way because in my case I have 35 tables so creating the dataflow from within the warehouse all tables destination is automatically set to that warehouse only . I need not to define destination for each table , but here for all table update method sets to append I cant see the way to change it


If you have any knowledge on this It will be a great help.

Thanks
Rahul Sharma

[v-tsaipranay · Accepted solution]

Hi @IAMCS ,

Thank you for reaching out to the Microsoft fabric community forum.

You're correct, when creating a Dataflow within a warehouse, the destination is auto assigned, which is efficient for bulk ingestion. However, this method currently does not expose options for Update Method (defaults to Append) or Column Mapping. This is expected behavior in Fabric’s current design.

To modify the Update Method (e.g., set to "Replace") and configure column mappings, you'll need to create the Dataflow at the workspace level. While this requires manual destination assignment for each table, it's currently the only supported way to access full configuration options.

We understand this limitation and recommend submitting feedback via Fabric Ideas - Microsoft Fabric Community

.

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

Thankyou.