As organizations grow their data and AI capabilities, Databricks deployments often expand beyond a single workspace. Multiple teams work in parallel, each with their own Databricks environments. This setup creates challenges in managing dependencies, sharing resources, and maintaining consistency across workspaces. Without a clear way to coordinate these environments, teams risk duplication of effort, conflicting configurations, and inefficient workflows. The dataAI team at REDE Consulting...