How Pre-aggregation and Materialized Tables Can Slash BI Query Costs and Latency

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Pre-aggregation and materialized tables are key techniques for converting slow, expensive data warehouse queries into fast, sub-second BI API responses. Engineers are advised to choose between pre-computing and on-demand computation based on query frequency, scan cost, and freshness requirements, using a measurable break-even formula derived from query logs. Materializations should be designed to mirror how API consumers request data, with one rollup table per canonical access pattern rather than per individual dashboard. Multi-level rollups, covering columns, and denormalized joins help eliminate runtime latency spikes and unpredictable billing from repeated large scans. The approach treats materialization as a product capability with defined refresh schedules, security enforcement, and service-level agreements tied to data freshness.

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ProgrammingDEV Community ·

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