Prepare NoSQL data for machine learning and AI workflows while keeping Clojure transformations inspectable.
This section bridges the chapter overview and the detailed lessons below. For Java engineers, the practical question is how to handle machine learning and AI use of NoSQL data in Clojure code at the database boundary.
| Review focus | What to check |
|---|---|
| Data readiness | Normalize documents and events into model-friendly shapes. |
| Pipelines | Keep feature extraction repeatable in Clojure code. |
| Boundaries | Separate model calls from deterministic data preparation. |
Use the child lessons to move from concept to implementation. The section goal is to make the trade-off visible before the code hardens around a database assumption.