Describe data architecture for fast multi-dimensional slicing and pre-computation trade-offs
Tests analytical architecture trade-offs between latency and cost. Strong answers propose a hybrid pipeline: columnar warehouse for flexible exploration plus pre-aggregated OLAP cubes for sub-second dashboards.
Tests whether you can design an analytical data architecture that balances query performance, cost, and flexibility for multi-dimensional exploration. A strong answer describes a hybrid architecture: streaming ingestion into a columnar store like ClickHouse or Snowflake for flexible SQL exploration, paired with pre-computed OLAP cubes or materialized aggregates for high-cardinality, sub-second dashboard queries. It must contrast storage cost, data freshness, and query latency.
Read the original → Wikipedia: Data warehouse
- #analytics
- #data-warehouse
- #olap
- #columnar-storage
- #system-design
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