Purpose
- Move the final model into a production environment.
- Enable the model to generate actionable outputs, automate processes, or support decision-making.
- Ensure deployment is aligned with business context and prior analysis.
Key Considerations
- Use documentation from Data Understanding and Data Preparation to provide context, especially if deployment occurs long after initial data work.
- Ensure that deployment supports the intended business objectives and integrates seamlessly with existing systems.
- Maintain traceability and reproducibility of the model and its results.
Deployment Activities
- Integrate the model into operational systems or pipelines.
- Automate reporting or decision-support functions.
- Monitor model performance and maintain logs for updates or retraining.
Related Concepts
- Model Deployment: The broader process of operationalizing predictive or analytical models.
Outcome
- A working, production-ready model that delivers value and can be maintained over time.
- Documentation ensures understanding of model context, data sources, and preparation steps.