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You are developing a real-time prediction engine that processes streaming files. These files, which may contain personally identifiable information (PII), are ingested into Cloud Storage and eventually stored in BigQuery. To protect this sensitive data, you need to ensure that it is masked while still preserving its referential integrity, as names and emails are frequently used as join keys in your database. How can you utilize the Cloud Data Loss Prevention API (DLP API) to guarantee that the PII data is not accessible by unauthorized individuals?
A
Create a pseudonym by replacing the PII data with cryptogenic tokens, and store the non-tokenized data in a locked-down button.
B
Redact all PII data, and store a version of the unredacted data in a locked-down bucket.
C
Scan every table in BigQuery, and mask the data it finds that has PII.
D
Create a pseudonym by replacing PII data with a cryptographic format-preserving token.