Granularity describes the frequency at which the data warehouse is updated (e.g., real-time vs. nightly batch). The recommendation is to store multiple grains (e.g., daily transactions and monthly summaries) within the same physical fact table to allow users to switch between detailed and summary views without joining tables.

Granularity is the count of foreign keys present in the fact table schema. The recommendation is to design the fact table based on the primary key constraints of the source system, ensuring that the warehouse granularity strictly mirrors the operational system's primary keys to maintain data integrity.

Granularity refers to the number of dimensions linked to the fact table. The recommendation is to aggregate data to a higher level (e.g., monthly sales instead of individual transactions) during the ETL process to significantly reduce storage costs and improve query performance.

Granularity defines the specific business event or measurement represented by a single row in the fact table. The recommendation is to store data at the lowest possible (atomic) level of detail to ensure maximum analytical flexibility and the ability to roll up to any required summary.