As a GCP Cloud Architect, your objective is to optimize the expenses associated with a BigQuery setup, which is used for complex analytical queries. What strategy would you adopt to reduce costs without compromising on performance?

*Explanation: The best approach to minimize costs while maintaining performance in BigQuery is to optimize the queries to reduce the amount of data being scanned. BigQuery's pricing model is primarily based on the amount of data processed by each query. Therefore, optimizing queries to be more efficient and scan only the necessary data can lead to significant cost savings. Techniques for query optimization include using proper filtering criteria, avoiding SELECT *, and using partitioned and clustered tables effectively. This not only reduces the amount of data scanned but also speeds up the query execution time, contributing to overall performance efficiency. While other options like on-demand pricing or off-peak hour execution might seem appealing, they do not address the core issue of data usage efficiency like query optimization does. Therefore, focusing on refining queries is the most direct and effective strategy for cost optimization in BigQuery.*