Topic 1 Question 300
You work for a bank. You need to train a model by using unstructured data stored in Cloud Storage that predicts whether credit card transactions are fraudulent. The data needs to be converted to a structured format to facilitate analysis in BigQuery. Company policy requires that data containing personally identifiable information (PII) remain in Cloud Storage. You need to implement a scalable solution that preserves the data’s value for analysis. What should you do?
Use BigQuery’s authorized views and column-level access controls to restrict access to PII within the dataset.
Use the DLP API to de-identify the sensitive data before loading it into BigQuery.
Store the unstructured data in a separate PII-compliant BigQuery database.
Remove the sensitive data from the files manually before loading them into BigQuery.
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- 正解だと思う選択肢: B
B. Use the DLP API to de-identify the sensitive data before loading it into BigQuery. Why Option B? Ensures Compliance with Company Policy
Company policy requires PII to remain in Cloud Storage. Google Cloud Data Loss Prevention (DLP) API can de-identify (mask, tokenize, or redact) PII while preserving its analytical value. Only de-identified structured data is moved to BigQuery, ensuring compliance. Preserves Data Utility for Analysis
DLP API supports format-preserving encryption (FPE) and tokenization, allowing analysis without exposing sensitive details. Fraud detection models can still leverage de-identified transaction patterns without accessing raw PII. Scalable and Automated Solution
DLP API can be used in a Dataflow pipeline to process large amounts of unstructured data before ingestion. Avoids manual effort (as required in Option D) and provides consistent security measures.
👍 2tk7867862025/02/19 - 正解だと思う選択肢: B
B. This is the most effective and scalable solution. The DLP (Data Loss Prevention) API is designed to identify and transform sensitive data.
👍 1CassiniExam2025/02/27
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