To scale Databricks SQL to 2,000 users efficiently and cost-effectively, we adopted serverless, ensuring dynamic scalability and resource optimization. During peak times, resources scale up automatically; during low demand, they scale down, preventing waste. Additionally, we implemented a strong content governance model. We created continuous monitoring to assess query and dashboard performance, notifying users about adjustments and ensuring only relevant content remains active. If a query exceeds time or impact limits, access is reviewed and, if necessary, deactivated. This approach brought greater efficiency, cost reduction and an improved user experience, keeping the platform well-organized and high-performing.

With massive data volume and complexity, scaling data governance became a significant challenge. Centralizing metadata management, ensuring regulatory compliance and controlling data access across multiple platforms turned to be critical to maintaining efficiency and trust.