Star schema
The classic data-warehouse model: a central fact table (measures, e.g. sales) surrounded by dimension tables (time, product, customer, store). The shape resembles a star. Ralph Kimball's design method for business intelligence.
Fact table: one row per event, with foreign keys to dimensions + numeric measures (amount, quantity). Dimension tables: descriptive attributes, deliberately denormalized for read speed. Trade-off: redundancy (the same category name repeats) is exchanged for fewer joins → fast aggregation queries. Distinct from a snowflake schema (dimensions normalized into several levels). BI tools (Power BI, Tableau, Looker) are optimized for the star schema. Still standard in modern cloud data warehouses (Snowflake, BigQuery) despite cheap storage.