A data engineer has multiple Unity Catalog-managed Delta tables that require regular maintenance.

Option A enables predictive optimization, which is designed to eliminate manual maintenance scheduling for Unity Catalog managed tables. Databricks evaluates table activity and automatically runs operations such as OPTIMIZE, VACUUM, and ANALYZE when beneficial, using serverless jobs compute. Predictive optimization can be enabled at multiple hierarchy levels, allowing tables to inherit the applicable setting. Auto Loader schema evolution handles changes in incoming file schemas but does not schedule table optimization. Liquid clustering improves data organization and query pruning, but it does not independently provide automated stale-file removal. Optimized writes and auto compaction reduce the creation of small files during write operations, but they do not replace adaptive VACUUM scheduling and the broader maintenance capabilities of predictive optimization. Therefore, option A directly satisfies the requirement for platform-managed table maintenance.

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