Describe star and snowflake schemas and their trade-offs
WHAT IT TESTS: Dimensional modeling denormalization trade-offs. ANSWER OUTLINE: Star schemas flatten dimensions for fast joins; snowflake schemas normalize hierarchies to reduce redundancy but add joins.
WHAT IT TESTS: Whether you understand the practical trade-offs between query performance, storage efficiency, and model simplicity in dimensional data warehouses. ANSWER OUTLINE: Star schemas surround a central fact table with denormalized dimension tables, minimizing joins and optimizing for read-heavy analytical workloads; snowflake schemas further normalize those dimensions into linked sub-tables, reducing data duplication but increasing query complexity and join overhead.
Read the original → Wikipedia: Star schema
- #dimensional modeling
- #data warehousing
- #star schema
- #snowflake schema
- #analytics
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