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Answer: Configure a BigQuery Omni connection to AWS S3 bucket data. Establish BigLake tables over both Cloud Storage and S3 data, enabling direct queries through BigQuery.
**Correct Answer: B** - **BigQuery Omni** facilitates seamless querying across multi-cloud environments, allowing data in both Cloud Storage and AWS S3 to be queried via BigQuery without direct access to the storage buckets. - **BigLake tables** provide the necessary abstraction layer, enabling querying without exposing the underlying storage buckets. **Why other options are incorrect:** - **A & D** suggest using external tables, which necessitate direct access to storage buckets, contrary to the requirement. - **C** involves unnecessary data transfer from AWS S3 to Cloud Storage, adding complexity and cost without addressing the multi-cloud querying need directly.
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Your organization uses a multi-cloud data storage strategy, leveraging both Google Cloud Storage and AWS S3 buckets within US regions to store data. The objective is to enable data access through BigQuery, regardless of the cloud where the data resides, while restricting direct access to the storage buckets. How can you facilitate users to query tables in BigQuery without granting them direct access to the underlying storage buckets?
A
Utilize the Storage Transfer Service to migrate data from AWS S3 buckets to Cloud Storage. Establish external tables over the Cloud Storage data and query directly via BigQuery.
B
Configure a BigQuery Omni connection to AWS S3 bucket data. Establish BigLake tables over both Cloud Storage and S3 data, enabling direct queries through BigQuery.
C
Employ the Storage Transfer Service to copy data from AWS S3 to Cloud Storage. Create BigLake tables over the Cloud Storage data for direct querying in BigQuery.
D
Set up a BigQuery Omni connection to AWS S3 bucket data. Create external tables over Cloud Storage and S3 data for direct querying in BigQuery.