Error response
Common causes
- Missing required columns — The dataset is missing columns that the connector requires
- Incompatible column types — A column exists but its data type does not match what the connector expects
- Schema structure mismatch — The dataset’s overall schema structure does not align with the connector’s input requirements
How to resolve
- Check the
detailfield — It describes the specific incompatibility between your dataset schema and the connector - Review connector requirements — Each connector expects a specific schema structure; verify your dataset matches
- Update your dataset schema — Modify the dataset to include the required columns with compatible data types
- Try a different connector — If the dataset cannot be modified, use a connector that supports the dataset’s schema
Error response fields
| Field | Description |
|---|---|
type | Link to this documentation page |
title | Brief description of the schema incompatibility |
status | 400 — indicates a client request validation error |
detail | Specific explanation of which columns or types are incompatible |
instance | The API endpoint that produced the error |
logId | Unique identifier for support requests |
Related content
Connectors
Reference for available connectors and their requirements
Datasets
Understand dataset schemas and structure
Error Reference
Overview of common API errors

