Skill UI

This guide provides a comprehensive method for setting up Snowflake observability. It teaches how to leverage built-in ACCOUNT_USAGE views to monitor critical metrics such as query performance (latency, error rates), credit consumption, and storage growth. Furthermore, it demonstrates how to implement automated alerts for operational issues (e.g., high failure rates, stuck warehouses) and export metrics to external monitoring systems like Grafana or Prometheus.

This comprehensive checklist guides the deployment of Snowflake data pipelines and integrations into a production environment. It covers critical areas such as authentication best practices, warehouse configuration, data pipeline readiness, access control, monitoring setup, and disaster recovery planning. Use it when preparing for a go-live or validating the stability of your production Snowflake setup.

This guide provides comprehensive instructions on managing performance and concurrency within Snowflake. It covers key concepts like warehouse sizing, multi-cluster configuration, and detecting query queuing issues. Users learn how to right-size resources and implement application-level rate limiting to prevent throttling and optimize data warehouse throughput for complex analytics workloads.

This skill simulates a Chief Data Officer's deep interrogation, pressure-testing any plan touching core data strategy. Use it before approving ML model training runs, selecting data infrastructure (warehouse vs. mesh), productizing data assets, or making major team hires. It ensures that all data decisions are grounded in clear business decisions, compliance, and structural necessity.

A static analysis tool that audits SQL code for common cost and performance anti-patterns (e.g., full-table scans, Cartesian joins). It calculates a query health score (0-100) for data warehouses like BigQuery, Snowflake, and Redshift, providing a prioritized, actionable plan with concrete fixes and estimated cost savings. Essential for FinOps and data quality assurance.

This skill analyzes your data warehouse to pinpoint stale, unused, or redundant tables that contribute to unnecessary storage costs. It classifies waste patterns (e.g., Zombie, Temporary) and computes safety tiers, helping users understand which assets can safely be dropped or archived to optimize spending and improve data governance.