BigQuery Infrastructure Audit
Audited and optimized a 10TB+ BigQuery data warehouse, reducing costs by 40% and improving query performance across 200+ scheduled queries.
Technologies Used
Key Features
Project Overview
Conducted a comprehensive audit of a 10TB+ BigQuery data warehouse, identifying cost inefficiencies and performance bottlenecks across 200+ scheduled queries.
The Challenge
Monthly BigQuery costs had grown 3x in a year without a corresponding increase in data volume. Query performance was degrading, scheduled jobs were timing out, and nobody had a clear picture of what was happening inside the warehouse.
What I Did
Systematic audit and optimization:
- Cost Analysis: Mapped every query to its business purpose and identified redundant, orphaned, and inefficient jobs consuming the majority of compute
- Schema Optimization: Restructured key tables with proper partitioning and clustering, reducing scan volumes by up to 80% for common query patterns
- Query Rewriting: Optimized the top 50 most expensive queries, replacing anti-patterns with efficient alternatives
- Governance: Implemented cost controls, automated anomaly alerts, and documentation for the data team
Outcome
Monthly BigQuery spend dropped 40% within the first billing cycle after changes were deployed. Average query performance improved significantly, and scheduled job timeouts were eliminated. The data team now has visibility into costs and performance through automated dashboards.