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Answer: Develop a Cloud Function that reads topics and calls the Cloud Data Loss Prevention (Cloud DLP) API, using tagging and confidence levels to pass or quarantine data in a bucket for review.
The optimal solution is **D**. Developing a Cloud Function that interacts with the Cloud DLP API offers a scalable, efficient method to prevent PII transmission. It analyzes data in real-time, leveraging Google Cloud's managed services for data security. **Option A** is less ideal due to the overhead of third-party tools and potential integration challenges. **Option B** is reactive, analyzing data post-transmission without preventing PII exposure. **Option C** restricts access but doesn't prevent PII from being transmitted initially.
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You are tasked with developing a scalable, cloud-native solution to prevent the transmission of personally identifiable information (PII) from handheld scanners to analytics systems for a shipping company. Which approach should you take?
A
Install a third-party data validation tool on Compute Engine virtual machines to check incoming data for sensitive information.
B
Use Cloud Logging to analyze data throughout the pipeline to identify transactions that may contain sensitive information.
C
Create an authorized view in BigQuery to restrict access to tables with sensitive data.
D
Develop a Cloud Function that reads topics and calls the Cloud Data Loss Prevention (Cloud DLP) API, using tagging and confidence levels to pass or quarantine data in a bucket for review.
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