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SAP-C03 practice question: Data lakes, lakehouses and data sharing (Lake Formation, Iceberg, Clean Rooms)

Architecture Design and Implementation Built for the Cloud A free question from our original SAP-C03 practice exam. Try it, then open the answer to see why each option is right or wrong.

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A retailer keeps its sales history as Apache Iceberg tables in an Amazon S3 data lake, owned by the merchandising account and cataloged in AWS Glue. The finance account needs to query sales tables with Amazon Athena, but it must not see the customer columns in those tables.

The data owner's team does not want copies of the data in other accounts, because copies drift from the source. The retailer also needs one place to see who has access to each column.

Which solution meets these requirements?

Choose one answer.

  1. A. Run a nightly AWS Glue job that copies the sales tables into an S3 bucket in the finance account and removes the customer columns during the copy, and catalog the copy there for Athena.
  2. B. Add a bucket policy to the merchandising bucket that lets the finance account's role read every object under the sales prefix. Athena then reads the Iceberg files directly.
  3. C. Grant the finance account access through AWS Lake Formation with column-level permissions on the sales tables. Create resource links to those tables in the finance account's Glue catalog, so Athena queries the source data.
  4. D. Load the sales tables into an Amazon Redshift Serverless namespace in the finance account every night, and grant column-level access to the finance users inside Redshift.
Show the answer and explanation

Answer: C

  • A. Wrong: Nightly copies create a second dataset that can drift from the source, which the data owner wants to avoid. Removing columns in each copy also spreads the access rules across two places.
  • B. Wrong: A bucket policy grants read access to whole objects, so the customer columns inside the Iceberg files would be readable. Column-level restrictions are not available through the bucket policy.
  • C. Right: Correct. Lake Formation applies column-level grants on the source tables across accounts, so the customer columns stay hidden. Resource links let Athena in the finance account query the single source without making a copy.
  • D. Wrong: This design hides the columns, but it loads a second copy of the data each night. It also moves the queries off the lake that the finance team uses through Athena.

Explanation

Lake Formation cross-account grants with column permissions and resource links give column-level access to one source with no copies. Bucket policies cannot restrict columns, and nightly copies or a warehouse load create drift and a second place to manage access.

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