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An analytics team maintains an interactive executive dashboard that frequently executes heavy aggregate calculations across a multi-terabyte transactional table in BigQuery. The table continuously receives new streaming appends throughout the day, and dashboard users are experiencing slow query performance and high computational costs from repeated aggregate calculations.
The team needs to reduce query latency and computational load by precalculating common aggregations while ensuring queries automatically serve real-time, consistent data without requiring any modifications to the dashboard SQL queries.
Which strategy should the team implement?
A BigQuery materialized view is a precomputed view that periodically or incrementally evaluates and stores the results of a query definition for improved performance and efficiency. Unlike standard virtual views, materialized views persist precalculated results—such as aggregated metrics, filters, and complex joins—directly in BigQuery storage, avoiding redundant query execution over massive underlying datasets.
Materialized views provide the best balance of precalculated performance gains, real-time consistency on streaming base data, and zero-maintenance transparency for downstream visualization tools.
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