Dataiku DSS

Overview

This node integrates with the Dataiku DSS API, enabling users to perform a wide range of operations on Dataiku DSS resources directly from n8n workflows. Specifically, for the Machine Learning - Lab resource and the Delete Visual Analysis operation, the node allows users to delete a visual analysis within a specified project and analysis context.

Common scenarios where this node is beneficial include automating the management of machine learning projects in Dataiku DSS, such as cleaning up obsolete visual analyses, managing ML tasks, or integrating model lifecycle steps into automated pipelines.

For example, a user might automate the deletion of outdated visual analyses after retraining models or archiving project data, ensuring that the workspace remains clean and relevant.

Properties

Output

The node outputs the response from the Dataiku DSS API call. For the Delete Visual Analysis operation, the output will typically confirm the successful deletion or provide error details if the operation fails.

• The output JSON contains the API response parsed from the server.
• No binary data output is expected for this operation.

Example output (success confirmation):

{
  "status": "Visual analysis deleted successfully"
}

Dependencies

• Requires an active connection to a Dataiku DSS instance.
• Requires valid API credentials (an API key) for authentication with the Dataiku DSS API.
• The node expects the Dataiku DSS server URL and user API key to be configured in the credentials.

Troubleshooting

• Missing Credentials Error: If the API key credential is not provided or invalid, the node will throw an error indicating missing credentials.
• Required Parameter Missing: The node validates required parameters like Project Key and Analysis ID. Omitting these will cause errors specifying which parameter is missing.
• API Errors: If the API call fails (e.g., due to network issues, permission problems, or non-existent visual analysis), the node throws an error with the message returned by the Dataiku DSS API.
• Unexpected Response Format: If the API returns a non-JSON response or unexpected content, the node attempts to handle it gracefully but may output raw text or an error.

To resolve common issues:

• Ensure all required parameters are correctly set.
• Verify API credentials and permissions.
• Check the existence of the visual analysis before attempting deletion.
• Review the Dataiku DSS server logs for detailed error information if API calls fail.

Links and References

• Dataiku DSS API Documentation
• Dataiku DSS Machine Learning Lab API Reference
• n8n Documentation on Creating Custom Nodes