Your organization is leveraging BigQuery for data analytics. You're responsible for optimizing costs. Which of the following practices would most effectively reduce query costs in BigQuery?

*Explanation:* Use partitioned tables and filter queries accordingly. One of the most effective cost optimization practices in BigQuery is to use partitioned tables and apply filters to queries. Partitioned tables allow you to reduce the amount of data scanned when querying, which directly translates to lower query costs. Storing data in Cloud Storage and using federated queries can increase costs due to data transfer fees. BigQuery ML and Cloud Dataflow have their use cases but may not directly reduce query costs. Using BigQuery Data Transfer Service to import only necessary data doesn't impact query costs, as query costs are primarily related to the amount of data scanned during query execution.