Question-18: Streaming, data engineering, and machine learning analytics are all completely linked with the Data Warehouse. It offers a standardized architecture that protects all of your data and information and gives you control over it, regardless of whether it is stored on private clouds, numerous public clouds, or hybrid clouds. You are developing a Data Warehouse on Google Cloud, and you would want to keep private data in BigQuery. It is a requirement of your employer that you produce the encryption keys outside of the Google Cloud. You are going to need to put a solution into action. What action should you take?
A. Produce a brand-new key with the Cloud Key Management Service (Cloud KMS). Keep all of your information in Cloud Storage by selecting the customer-managed key option and using the key that you just produced. In order to decrypt the data and save it in a new BigQuery dataset, you will need to build up a Dataflow pipeline.
B. Create a new key in Cloud KMS by generating it. Create a dataset in BigQuery by selecting the customer-managed key option, and then choose the key that you just made.
C. Bring an existing key into Cloud KMS. Keep all of your information in Cloud Storage by selecting the customer-managed key option and using the key that you just produced. In order to decrypt the data and save it in a new BigQuery dataset, you will need to build up a Dataflow pipeline.
D. Bring an existing key into the Cloud KMS. Create a dataset in BigQuery by selecting the customer-supplied key option, and then choose the key that you just made.

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