You work for a shipping company that uses handheld scanners to read shipping labels. Your company has strict data privacy standards that require scanners to only transmit recipients' personally identi

Question

Options

• ACreate an authorized view in BigQuery to restrict access to tables with sensitive data.
• BInstall a third-party data validation tool on Compute Engine virtual machines to check the incoming data for sensitive information.
• CUse Stackdriver logging to analyze the data passed through the total pipeline to identify transactions that may contain sensitive information.
• DBuild a Cloud Function that reads the topics and makes a call to the Cloud Data Loss Prevention API.

• A
  3% (1)
• B
  8% (3)
• C
  19% (7)
• D
  70% (26)

Explanation

Option D is correct because Cloud Functions provide a serverless, scalable event-driven mechanism to intercept data in motion, and the Cloud Data Loss Prevention (DLP) API is purpose-built to detect and redact PII - making this the fastest cloud-native path to scrubbing sensitive data before it reaches analytics systems.

Why the distractors fail:

• A (BigQuery authorized view) restricts who sees data after it's already stored - it doesn't prevent PII from being transmitted to analytics in the first place.
• B (third-party tool on Compute Engine) requires provisioning and managing VMs, violating the "scalable, managed services" requirement and adding operational overhead.
• C (Stackdriver/Cloud Logging) is a monitoring and observability tool - it can identify transactions with PII after the fact, but cannot prevent transmission of that data.

Memory tip: Think "intercept and inspect" - DLP + Cloud Functions acts as a gate in the pipeline, whereas BigQuery views and logging act after data has already flowed through. When a question asks to prevent exposure, the answer must act before data lands at its destination.

No community discussion yet for this question.