Built an intelligent system to monitor data quality, availability, and table usage in Snowflake. Generated dependency graphs, enabled impact analysis, and identified unused tables for cleanup. Enabled natural language querying for debugging and insights using LLMs. Reduced manual effort by 60%. Key Features: 📊 Data quality and availability monitoring 🔍 Table usage tracking and analytics 🗺️ Dependency graph generation 💥 Impact analysis for data changes 🧹 Unused table identification for cleanup 💬 Natural language querying using LLMs ⚡ 60% reduction in manual debugging effort The platform provides comprehensive insights into Snowflake data warehouses, helping teams maintain data quality, optimize storage, and quickly debug issues through intelligent automation and LLM-powered natural language interfaces.