Answer: Partition table data by `create_date` cluster table data by `location_id` and `device_version`

## Explanation **Option B is correct** because: - **Partition by `create_date`**: Date-based partitioning is ideal for time-series data as it allows BigQuery to scan only relevant partitions during queries - **Cluster by `location_id` and `device_version`**: Clustering organizes data within partitions, enabling efficient filtering and sorting - **Cost optimization**: Partitioning reduces the amount of data scanned, directly lowering query costs - **Performance optimization**: Clustering improves query performance by organizing data for common filter patterns **Why other options are incorrect**: - **Option A**: You cannot partition by multiple columns in BigQuery - only one partition column is allowed - **Option C**: Clustering alone doesn't provide the same cost benefits as partitioning for time-based queries - **Option D**: This has incorrect syntax (`locationed` instead of `location_id`) and partitions by non-date columns which is less efficient This combination of partitioning and clustering follows BigQuery best practices for optimizing both cost and performance.

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