Databricks

Databricks is a modern data and AI platform built around the lakehouse approach, designed to unify data storage and analytics. It helps teams build reliable pipelines for reporting, machine learning, and data products—using SQL, notebooks, and managed compute—so insights stay consistent across tools. Databricks is widely trusted for enterprise-scale analytics, governed data collaboration, and operationalizing AI workflows.

With Databricks connected, BOBs can treat your lakehouse as a source of truth and autonomously operate the compute and data layers that power analytics. From operational prompts (“rebuild the index,” “run the refresh now,” “tighten warehouse permissions,” “repair a failed pipeline”), BOBs can control warehouses and jobs, keep Vector Search indexes current, and query results when needed—so downstream reporting and AI retrieval stay aligned. This unlocks end-to-end use cases like automated insight pipelines, recurring refresh and backfills, self-healing data jobs, controlled warehouse provisioning, and governance across teams. Instead of waiting for engineers to manually run notebooks or manage infrastructure, BOBs can continuously maintain data products (including vector indexes) and execute structured SQL workloads on demand. Available actions and capabilities include: upsert vector search index data; sync/scan/query/manage Vector Search indexes (create, get, list, export, delete, delete data, repair, repair runs); full job lifecycle management (create, update, reset, run now, cancel, cancel all, repair run, delete, get, list, permissions); SQL warehouse lifecycle and governance (create/edit/delete, start/stop, list/get, set permissions, set config, get config/permissions, set permissions); and endpoint management (create, get, list, delete).