You're migrating a transactional dataset to BigQuery and need to choose an optimal schema design for performance. The table logs purchase details across various store locations, including: Transaction timestamp Items purchased Store ID City and State of the store You frequently run analytical queries to: Count items sold in the last 30 days Analyze purchase trends by state, city, and store To ensure optimal query performance, especially for time-based and location-based filtering, how should you structure your BigQuery table?