Google Professional Machine Learning Engineer
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You are training a machine learning model with data from BigQuery that contains Personally Identifiable Information (PII). You must reduce the dataset's sensitivity for training, but all columns are essential for the model. What is the correct approach?
A
Using Dataflow, ingest the columns with sensitive data from BigQuery, and then randomize the values in each sensitive column.
B
Use the Cloud Data Loss Prevention (DLP) API to scan for sensitive data, and use Dataflow with the DLP API to encrypt sensitive values with Format Preserving Encryption.
C
Use the Cloud Data Loss Prevention (DLP) API to scan for sensitive data, and use Dataflow to replace all sensitive data by using the encryption algorithm AES-256 with a salt.
D
Before training, use BigQuery to select only the columns that do not contain sensitive data. Create an authorized view of the data so that sensitive values cannot be accessed by unauthorized individuals.