A company uses Dataplex to manage data assets. The security team needs to ensure that only users with a specific IAM role can access data tagged as `confidential` in BigQuery. What should you do?

Grant the IAM role to the BigQuery dataset directly.

Use Dataplex to apply a tag to the data and create an IAM condition that checks for the tag.

Use Cloud IAM to create a custom role and assign it to the data.

Use BigQuery column-level security with policy tags.

A retail company stores raw clickstream events in Cloud Storage and loads them into BigQuery for daily analytics. The data governance team requires that any deletion of source files in Cloud Storage be automatically reflected in BigQuery so downstream reports never reference deleted data. They also need to track which pipeline job performed the deletion for audit purposes. What should you configure?

Enable BigQuery table snapshots and create a scheduled snapshot before each load job.

Configure a Cloud Storage notification on the bucket and use a Cloud Function to delete matching rows from BigQuery, logging the job ID.

Set up a BigQuery transfer service to re-ingest the bucket contents every hour, overwriting the table.

Use Cloud Storage Object Lifecycle rules to delete files and rely on BigQuery's automatic metadata sync.

A company is designing a data platform with a data lake in Cloud Storage and a data warehouse in BigQuery. The data engineering team wants to ensure that data in the lake is discoverable and governed, while data in the warehouse is used for high-performance analytics. What should they use?

Use Dataplex to manage the data lake and BigQuery for the warehouse.

Use Dataproc for both the lake and the warehouse.

Use Cloud Storage for both the lake and the warehouse.

Use BigQuery for both the lake and the warehouse.

What is the primary role of Dataplex in a Google Cloud data platform?

To provide a centralized platform for discovering, managing, and governing data across distributed systems

To orchestrate data pipelines and workflows

To serve as a data warehouse for structured analytical data

To provide a serverless compute platform for running data processing jobs

A company is designing a data platform that will store raw, unstructured files in a data lake and then run analytical queries on structured, curated data. Which combination of Google Cloud services best fits this architecture?

Cloud Storage for the data lake and BigQuery for analytics

Cloud SQL for the data lake and Cloud Spanner for analytics

Bigtable for the data lake and Cloud Storage for analytics

Cloud Functions for the data lake and Dataflow for analytics

Google CloudProfessional Data Engineer

Domain 3Objective 4

3.4 Designing for a Data Platform PROFESSIONAL-DATA-ENGINEER Practice Questions (Page 4)

Part of the Storing the data domain, which accounts for ~20% of the PROFESSIONAL-DATA-ENGINEER exam. Google Cloud does not publish an official question count, but from its 120-minute exam (~50–80 total, ~10–16 in this domain), expect 3–4 from this objective — we provide 23 practice questions to prepare you well beyond it. (estimate)

23questions here

5free pages

6concepts

~20%of the exam

Questions 16–20

16application · medium
A company uses Dataplex to manage data assets. The security team needs to ensure that only users with a specific IAM role can access data tagged as `confidential` in BigQuery. What should you do?
Select an answer first
17application · medium
A retail company stores raw clickstream events in Cloud Storage and loads them into BigQuery for daily analytics. The data governance team requires that any deletion of source files in Cloud Storage be automatically reflected in BigQuery so downstream reports never reference deleted data. They also need to track which pipeline job performed the deletion for audit purposes. What should you configure?
Select an answer first
18application · medium
A company is designing a data platform with a data lake in Cloud Storage and a data warehouse in BigQuery. The data engineering team wants to ensure that data in the lake is discoverable and governed, while data in the warehouse is used for high-performance analytics. What should they use?
Select an answer first
19foundation · easy
What is the primary role of Dataplex in a Google Cloud data platform?
Select an answer first
20foundation · easy
A company is designing a data platform that will store raw, unstructured files in a data lake and then run analytical queries on structured, curated data. Which combination of Google Cloud services best fits this architecture?
Select an answer first

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