Fabric Dataflow Gen 2

[negideepika06]

I have one source account file from which I’m deriving 12 different tables in Dataflows, all of which are driven from the same account file.

For example, in the account file there is a column called SegmentAllocation that contains nested JSON. In my scenario, I’m expanding this JSON structure (which is sourced from the account file) into multiple columns/tables.

My dataflow runs successfully for all 12 derived tables plus the main account table. However, for 4 of these tables—whose destination is a Lakehouse—the entire table is populated with NULL values; every row shows NULL for all columns.

I’ve tried several troubleshooting steps:

• Dropping the destination tables and recreating them with the same schema as defined in the dataflow.

• Ensuring the schema fully matches both the dataflow and the Lakehouse destination.

• Re‑mapping the dataflow to the default data destination.

Despite all of this, these 4 tables still end up with completely NULL values.

[v-hashadapu]

Hi @negideepika06 , Hope you're doing okay! May we know if it worked for you, or are you still experiencing difficulties? Let us know — your feedback can really help others in the same situation.

[v-hashadapu]

Hi @negideepika06 , hope you are doing great. May we know if your issue is solved or if you are still experiencing difficulties. Please share the details as it will help the community, especially others with similar issues.

[v-hashadapu]

Hi @negideepika06 , Thank you for reaching out to the Microsoft Community Forum.

Since you’re expanding nested JSON, it’s worth validating the last few steps of those 4 queries to ensure they’re actually returning populated records and not empty structures. Also, double check the column to destination mapping in the Lakehouse, as mismatches there can result in all null writes without errors. Write one of the failing queries to a new table, if it still comes out NULL, the issue is in the transformation layer, if not, it’s in the Lakehouse write/mapping.

[lbendlin · Accepted solution]

Did you maybe forget to specify the column types before sending the results to the Lakehouse?