Playbook
Our ML team has outgrown notebooks and needs a proper lakehouse
A retail bank's ML team is running models in fragmented Databricks workspaces with no central governance. They need Unity Catalog, MLflow lifecycle management, and a path to production GenAI on the same data substrate.
Trigger — ML production incidents; regulator wants lineage and access auditing.
Good outcome — Unity Catalog tenant-wide, DBCU commitment sized to forecast, MLflow + Mosaic AI in production.