You are working with a data warehousing team that performs data analysis. The team needs to process data from external partners, but the data contains personally identifiable information (PII). You need to process and store the data without storing any of the PIIE data. What should you do?

The correct option leverages Dataflow for scalable data processing and Cloud DLP for PII identification and redaction, ensuring that sensitive information is removed before storage in BigQuery. This directly addresses the requirement to process and store data without storing PII. Storing PII in a separate Cloud Storage bucket, even with a retention policy, still means you are storing PII, which the requirement explicitly forbids. Asking partners to upload directly to Cloud Storage and then processing is less efficient than a direct Dataflow pull if the source is an API or database, and doesn't change the core PII handling. Asking partners to import directly into BigQuery and then skipping columns in a pipeline is problematic because the PII would already be in BigQuery, violating the "without storing any PII" rule. Cloud DLP is the key service for PII redaction.