I have two different datasets that will be used to train two separate regression models Each dataset has its own preprocessing steps, and the models will have independent training pipelines.
What best practice approach for organizing Databricks Asset Bundles (DABs) in this scenario? Specifically, Iām wondering whether itās better to create one DAB per model and dataset or to combine everything into a single DAB for simplicity.
Additionally, any insights on structuring the MLOps pipeline for model registry, deployment, and monitoring in such a setup would be greatly appreciated.
DAB will be on a monorepo for new use case
