GCP Professional Data Engineer Practice Question

Your organization has subscribed to a private listing in Analytics Hub that a partner publishes. The subscription automatically created a read-only linked dataset called ecommerce_partner.default in your analytics project. Several business analysts need to build Looker Studio dashboards that query this data, and you want to avoid additional storage cost or data-movement operations. Which action enables the analysts to visualize the shared data while following Google-recommended architecture and keeping operational overhead minimal?

Schedule a daily BigQuery Data Transfer Service job that copies all tables from the linked dataset into a native dataset, then connect Looker Studio to the copied tables.
Trigger a Cloud Function each night to export the linked tables as CSV files to Cloud Storage and use Looker Studio's Cloud Storage connector to build reports.
Have analysts create a BigQuery data source in Looker Studio that points directly to the linked dataset, and grant them BigQuery Data Viewer on the dataset plus BigQuery Job User on the project.
Set up scheduled queries that write the linked data into Cloud SQL, and configure Looker Studio to read from the Cloud SQL instance instead of BigQuery.

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Answer Description

The linked dataset is already a first-class BigQuery dataset in the consumer project, backed by tables that physically reside in the publisher's project. Looker Studio natively connects to BigQuery through the BigQuery API, so it can query the linked dataset directly without copying or exporting data. Analysts simply need permission to read the dataset (roles/bigquery.dataViewer) and to run query jobs that bill the consumer project (roles/bigquery.jobUser). No data transfer, export, or replication jobs are required, eliminating extra storage cost and maintenance. Copying tables, exporting to Cloud Storage, or materializing data in Cloud SQL introduce unnecessary cost and operational complexity and therefore are not recommended for consuming Analytics Hub exchanges.

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