A group of data scientists have uploaded multiple time-series datasets to BigQuery over the last year. They have noticed that their queries—which select up to six columns, apply four SQL functions, and group by the day of a timestamp—are taking longer to run and are incurring higher BigQuery costs as they add data. They do not understand why this is the case since they typically work only with the most recent set of data loaded. What would you recommend they consider in order to reduce query latency and query costs?