Exam Professional Data Engineer topic 1 question 244 discussion

Actual exam question from Google's Professional Data Engineer

Question #: 244
Topic #: 1

[All Professional Data Engineer Questions]

Different teams in your organization store customer and performance data in BigQuery. Each team needs to keep full control of their collected data, be able to query data within their projects, and be able to exchange their data with other teams. You need to implement an organization-wide solution, while minimizing operational tasks and costs. What should you do?

A. Ask each team to create authorized views of their data. Grant the biquery.jobUser role to each team.
B. Create a BigQuery scheduled query to replicate all customer data into team projects.
C. Ask each team to publish their data in Analytics Hub. Direct the other teams to subscribe to them.
D. Enable each team to create materialized views of the data they need to access in their projects.

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Suggested Answer: C 🗳️

by rahulvin at Dec. 30, 2023, 6:24 p.m.

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raaad

Highly Voted 11 months, 2 weeks ago

Selected Answer: C

- Analytics Hub allows organizations to create and manage exchanges where producers can publish their data and consumers can discover and subscribe to data products. - Asking each team to publish their data in Analytics Hub and having other teams subscribe to them is a scalable and controlled way of sharing data. - It minimizes operational tasks because data doesn't need to be duplicated or manually managed after setup, and teams can maintain full control over their datasets.

upvoted 5 times

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CGS22

Most Recent 8 months, 1 week ago

Selected Answer: C

Why C is the best choice: Centralized Data Exchange: Analytics Hub provides a unified platform for data sharing across teams and organizations. It simplifies the process of publishing, discovering, and subscribing to datasets, reducing operational overhead. Data Ownership and Control: Each team retains full control over their data, deciding which datasets to publish and who can access them. This ensures data governance and security. Cross-Project Querying: Once a team subscribes to a dataset in Analytics Hub, they can query it directly from their own BigQuery project, enabling seamless data access without data replication. Cost Efficiency: Analytics Hub eliminates the need for data duplication or complex ETL processes, reducing storage and processing costs.

upvoted 1 times

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