Databricks Certified Machine Learning Associate Practice Mode

Community Discussion

Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.

• Chose A0

  - Correct answer : A — Because the feature table lives in Unity Catalog, it is accessible to every workspace attached to the same metastore, so the marketing team can read and reuse it through a normal `catalog.schema.table` reference without copying data. A . Unity Catalog objects are scoped to the metastore, not to a single workspace, so any workspace attached to that metastore can query the table directly by its three-level name. This is exactly why account-level feature tables enable reuse across teams without duplicating pipelines. B . A workspace-level Hive metastore is scoped to a single workspace by definition, so it cannot grant account-wide access — this is the opposite of how workspace-level feature stores behave. It also inverts the premise of the question, which already states the table is account-level. C . The legacy `FeatureStoreClient` is workspace-scoped and does not propagate schemas into other workspaces' model registries; registry entries are not how table read access is granted. This mixes up model registry replication with the actual mechanism, metastore-level table access. D . Auto Loader is an ingestion tool for incrementally loading files into a table; it has no role in replicating a Unity Catalog table's files into other workspaces' DBFS mounts. This describes a mechanism that does not exist and misattributes cross-workspace access to the wrong feature.