The correct answer is C. Exporting Cloud Logging data directly to BigQuery allows for efficient storage and analysis in a scalable and cost-effective manner. Creating views in BigQuery enables filtering by specific criteria (project, log type, resource, and user), which is crucial for generating the requested daily reports. BigQuery's powerful querying capabilities facilitate quick processing of large datasets, offering insights into resource consumption and usage.

Why the other options are incorrect:

• A: Manually filtering and exporting data in CSV format is inefficient for daily reports and doesn't scale well with large datasets. CSV format also limits advanced analytics capabilities.
• B: This method adds unnecessary complexity by involving Cloud Storage and Dataprep for data cleansing, making the process less straightforward compared to direct BigQuery exports.
• D: Manually filtering and importing data into BigQuery is time-consuming and less efficient than directly exporting data to BigQuery.