Analyze BigQuery Usage

Expensive queries can be identified by analyzing BigQuery job logs to find queries consuming the most data and compute resources. This Skill scans your project's query history over a specified timeframe, ranks queries by cost, and flags inefficient patterns like full table scans, so you can optimize or eliminate high-cost operations.

Analyze BigQuery usage patterns by examining per-user activity and query execution logs to detect inefficient practices and cost drivers. This Skill aggregates usage data by user and query type, revealing who and what consume the most resources, enabling targeted optimization and cost governance.

Yes. This Skill automates BigQuery cost analysis by querying job metadata directly using the bq CLI, eliminating manual inspection. It requires only Cloud SDK authentication and bigquery.jobs.list permission to generate a structured optimization report with anti-patterns and actionable fixes.

BigQuery anti-patterns like unnecessary full-table scans and redundant queries waste cloud spending. This Skill detects these patterns by analyzing query execution details and data processed, then outputs specific recommendations to restructure queries, partition tables, or cache results for cost reduction.

To optimize BigQuery performance and costs, provide your GCP Project ID, desired analysis timeframe in hours, and ensure the bq CLI and Cloud SDK are installed with appropriate authentication. This Skill then accesses your query job history to generate insights without requiring manual data export.