How to Generate Encryption Keys for Storing Sensitive Data in BigQuery

D.

To store sensitive data in BigQuery, you can use a customer-managed encryption key to encrypt the data at rest. This allows you to control the encryption key and ensure that only authorized users can access your data.

To generate the encryption keys outside of Google Cloud, you can use a key management service like Cloud Key Management Service (Cloud KMS). Cloud KMS provides a secure and scalable way to manage and use cryptographic keys.

The correct answer to this question is D: Import a key in Cloud KMS. Create a dataset in BigQuery using the customer-supplied key option and select the created key.

Here's a detailed explanation of why this is the correct answer:

Option A is incorrect because it suggests storing the data in Cloud Storage, which is not necessary for storing data in BigQuery. Additionally, it suggests decrypting the data in a Dataflow pipeline, which adds unnecessary complexity to the solution.

Option B is also incorrect because it suggests creating a dataset in BigQuery using a customer-managed key. However, the requirement is to generate the encryption key outside of Google Cloud.

Option C is incorrect because it suggests importing a key in Cloud KMS and storing the data in Cloud Storage, which is not necessary for storing data in BigQuery. Additionally, it suggests decrypting the data in a Dataflow pipeline, which adds unnecessary complexity to the solution.

Option D is the correct answer because it suggests importing a key in Cloud KMS and creating a dataset in BigQuery using the customer-supplied key option. This allows you to use a key generated outside of Google Cloud to encrypt the data at rest in BigQuery. The customer-supplied key option is available when creating a dataset in BigQuery, and it allows you to specify the encryption key to use for the dataset. By selecting the created key in Cloud KMS, you can ensure that only authorized users can access the data.