You stream reporting data into BigQuery with staging and production tables. To maintain a single master dataset without impacting ingestion or reporting, how should you move staged data to production?

Moving staged data into production and then deleting the staging contents every three hours is the most appropriate strategy. This approach ensures that the production table always reflects the latest processed data from staging, maintaining a single master dataset. Deleting the staging contents after a successful move prevents data duplication and keeps the staging area clean for new incoming data without impacting ingestion. The three-hour interval provides a reasonable balance between data freshness and operational overhead, allowing for sufficient data accumulation in staging while ensuring timely updates to production. Options that only "update" production with changes from staging risk data inconsistencies if not carefully managed, as they don't explicitly address the full transfer and cleanup of staged data. The thirty-minute interval might be too frequent, leading to higher operational costs and potential resource contention without significant additional benefit for reporting data.