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Reduce BigQuery costs for a high-volume analytics workload. Strategies: 1. Partition tables by date and cluster by high-cardinality columns. 2. Use materialized views for frequently-run aggregations. 3. Implement query result caching and avoid SELECT *. 4. Set up cost controls with custom quotas per project. 5. Analyze query execution plans to identify expensive operations. Provide before/after cost comparison and ROI calculation. Include monitoring dashboard for ongoing cost tracking.