Snowflake's Semantic Views provide a governed business interface over raw tables, enabling AI-powered natural language querying via Cortex Analyst and consistent BI reporting. Best practices include using business-friendly terminology, writing detailed descriptions for all objects, adding synonyms for natural language variations, centralizing metric calculations, and managing definitions with dbt or YAML/Git. Key DOs include starting small with single-table views, using predictable alias names, leveraging Autopilot for bootstrapping, and setting up verified queries for unit testing. DON'Ts include skipping descriptions, using cryptic table names, treating the model as a one-time build, and relying solely on YAML semantic models instead of semantic views with RBAC and usage stats.
