Schema drift is inevitable in Snowflake, leading to missing or inconsistent data that compromises query and report accuracy. To track schema drift, users can generate and compare schema snapshots, use the Snowflake Community Python script (schemachange), leverage Snowflake's information_schema, or employ automated monitoring tools like Metaplane. By tracking schema changes, users can maintain data quality, integrity, and reliability while increasing trust in their organization's data systems.