You need to share aggregate results from a BigQuery dataset containing user-level tables with other projects while preventing access to raw user data, minimizing storage, and charging query costs to consuming projects. What should you do?

An authorized view is the correct solution because it allows you to grant access to the results of a query (the aggregate data) without exposing the underlying raw tables. This directly addresses the requirement of preventing access to raw user data. When a user queries an authorized view, the query costs are charged to the project containing the view, not the project with the underlying tables, fulfilling the cost allocation requirement. Authorized views also minimize storage as they don't store the aggregated data themselves; they execute the query on demand. Creating a new dataset and view is redundant and less efficient than an authorized view for this specific use case, as it implies moving or duplicating data. Creating a new dataset and table would involve storing the aggregated results, increasing storage costs and potentially leading to stale data. Creating dataViewer IAM roles on the dataset would grant access to the raw data, directly violating the requirement to prevent access to raw user data.