What are the different types of dimensions in dimensional modeling?

Dimensions are descriptive attributes that provide context to facts in a data warehouse. The main types of dimensions include: 1. Conformed dimensions – shared across multiple fact tables, ensuring consistency. 2. Business dimensions – represent business entities like Customer, Product, or Time. 3. Hierarchical dimensions – contain levels (e.g., Country > State > City) for drill‑down. 4. Degenerate dimensions – attributes that come from the fact table but are treated as dimensions (e.g., Order Number). 5. Slowly Changing Dimensions (SCD) – handle changes over time, with types 1, 2, 3, etc. 6. Junk dimensions – group unrelated low‑cardinality flags into a single dimension. 7. Role‑playing dimensions – a single dimension used in multiple roles (e.g., Employee used as Manager and Employee). Choosing the right type depends on the business requirement, data volume, and reporting needs. Conformed dimensions promote reuse; hierarchical dimensions enable drill‑down; SCDs preserve history; degenerate dimensions reduce joins. Understanding these types helps design efficient, maintainable dimensional models.