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You are employed at a shipping company that utilizes handheld scanners to read shipping labels. The company adheres to stringent data privacy standards, necessitating that scanners solely transmit tracking numbers when events are sent to Kafka topics. However, a recent software update has caused these scanners to mistakenly transmit recipients' personally identifiable information (PII) to analytics systems, thereby breaching user privacy rules. Your objective is to swiftly develop a scalable solution using cloud-native managed services to prevent the exposure of PII to the analytics systems. What actions should you take?
A
Create an authorized view in BigQuery to restrict access to tables with sensitive data.
B
Install a third-party data validation tool on Compute Engine virtual machines to check the incoming data for sensitive information.
C
Use Cloud Logging to analyze the data passed through the total pipeline to identify transactions that may contain sensitive information.
D
Build a Cloud Function that reads the topics and makes a call to the Cloud Data Loss Prevention (Cloud DLP) API. Use the tagging and confidence levels to either pass or quarantine the data in a bucket for review.