Dataiku DSS

Overview

This node integrates with the Dataiku DSS API to perform various operations related to machine learning saved models, specifically including computing subpopulation analyses of a saved model version. It is useful for users who want to automate interactions with Dataiku DSS projects and models within n8n workflows.

For the Machine Learning - Saved Model resource and the Compute Subpopulation Analysis of Version operation, the node triggers the computation of subpopulation analyses on a specific version of a saved machine learning model. This can help data scientists and ML engineers analyze how different subpopulations behave under the model, which is critical for fairness, bias detection, and detailed performance evaluation.

Practical Example

• You have a saved ML model in a Dataiku project and want to compute subpopulation analyses for a particular version programmatically.
• Using this node, you specify the project key, saved model ID, and version ID, then trigger the computation.
• The node calls the appropriate Dataiku DSS API endpoint to start the analysis, enabling integration into automated pipelines or monitoring systems.

Properties

Output

The node outputs the response from the Dataiku DSS API call in the json field of the output item. For the "Compute Subpopulation Analysis of Version" operation, this typically includes information about the launched computation task or the status/result of the subpopulation analysis.

If the operation involves downloading files or binary content (not applicable here), the node would output binary data accordingly, but for this operation, the output is JSON describing the triggered analysis.

Dependencies

• Requires an active connection to a Dataiku DSS instance.
• Needs 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 or server URL is not provided, the node will throw an error indicating missing credentials.
• Required Parameter Missing: The node validates required parameters such as Project Key, Save Model ID, and Version ID. Omitting any of these will cause an error.
• API Errors: If the Dataiku DSS API returns an error (e.g., invalid IDs, permission issues), the node will throw an error with the message returned by the API.
• JSON Parsing Errors: If the API response is not valid JSON when expected, the node attempts to handle it gracefully but may output raw text instead.

To resolve errors:

• Ensure all required input properties are correctly set.
• Verify that the API key has sufficient permissions.
• Confirm that the project, saved model, and version IDs exist and are accessible.
• Check network connectivity to the Dataiku DSS server.

Links and References

• Dataiku DSS API Documentation
• Subpopulation Analysis in Dataiku DSS
• n8n Documentation: Creating Custom Nodes

Note: This summary is based solely on static code analysis of the provided source and property definitions without runtime execution or external context.