AutoML in TIBCO Spotfire® with Amazon SageMaker Autopilot

This component enables Amazon SageMaker AutoPilot integration with TIBCO Spotfire.

Compatible Products

TIBCO Spotfire®


TIBCO Software

Compatible Versions

Created with TIBCO Spotfire 11.3

Python library versions used for testing:
● botocore - 1.20.61
● sagemaker - 2.35.0
● pandas - 1.2.4
● numpy - 1.20.2
● scikit-learn - 0.24.2 




For data scientists, Amazon SageMaker Autopilot eliminates the heavy lifting of building ML models, and helps them to automatically build, train, and tune the best ML model based on their data.

TIBCO Spotfire’s new SageMaker Autopilot integration brings these same benefits to everyone from within Spotfire. Now, without leaving Spotfire, users can:

  • Upload training data, define configurations, and kick off a SageMaker Autopilot job.
  • When modeling is complete, Spotfire automatically generates visualizations and model explainability ready for exploration, allowing you to see how well the "BestCandidate" model performed.
  • Once you are ready, you can deploy the model on new data in either batch mode or as an endpoint, which is most appropriate for your data.

For a closer look at the Spotfire integration with SageMaker Autopilot, checkout this demo.

To learn more on how to get started, checkout the Reference Info tab above.

For more information on Amazon SageMaker Autopilot, click here


Release 1.0.0

Published: April 2021

Initial release includes:

  • Dxp with example usage
  • Documentation
  • License information

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Welcome to the TIBCO AutoML with Sagemaker Community Wiki

Getting Started

The Amazon SageMaker Autopilot integration is made available in a DXP file. You can download this file as well as documentation from the Releases tab above.

View the Wiki Page