Data Processors

This tutorial explains how to define data processors — transformations that prepare and shape data for your optimisation model.

Note

This tutorial is a work in progress. Full content coming soon.

Overview

Data processors sit between your raw data sources and the model’s optimisation logic. They allow you to filter, aggregate, join, and transform data before it is consumed by the solver.

Key concepts:

• Input mappings — connecting data sources to processor inputs

• Transformations — filtering rows, computing derived values

• Output tables — the processed data available to the model

Next Steps

Continue with the Reports tutorial to learn how to surface results.