Crucial Exams

GCP Professional Data Engineer Practice Question

Your analytics platform stores several years of click-stream data in Parquet files on Cloud Storage. Data scientists query the most recent partitions interactively through BigQuery, but new compliance rules require user-specific row-level filters to be enforced on both the historic data in Cloud Storage and the fact tables already ingested into BigQuery. Engineering stipulates that you must:

  • Avoid copying or re-loading the Parquet data into new BigQuery tables.
  • Maintain a single, consistent security policy that governs data in both the warehouse and the lake.
  • Preserve the ability for future Spark jobs on Dataproc to read the same Parquet files directly. Which approach best meets these requirements while keeping operational overhead low?

  • Provide signed URLs protected by VPC Service Controls and instruct analysts to query the Parquet files with federated queries.

  • Create BigLake tables on the Parquet files and attach BigQuery row-level access policies so the same security model applies to both BigLake and existing native tables.

  • Load the Parquet partitions into new BigQuery managed tables and apply dataset-level IAM roles to enforce access controls.

  • Define BigQuery external tables on the Parquet objects and rely on Cloud Storage bucket-level IAM to restrict access to sensitive rows.

GCP Professional Data Engineer
Storing the data
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