Google Cloud Professional Data Engineer — Question 177

Your company operates in three domains: airlines, hotels, and ride-hailing services. Each domain has two teams: analytics and data science, which create data assets in BigQuery with the help of a central data platform team. However, as each domain is evolving rapidly, the central data platform team is becoming a bottleneck. This is causing delays in deriving insights from data, and resulting in stale data when pipelines are not kept up to date. You need to design a data mesh architecture by using Dataplex to eliminate the bottleneck. What should you do?

Answer options

• A. 1. Create one lake for each team. Inside each lake, create one zone for each domain. 2. Attach each of the BigQuery datasets created by the individual teams as assets to the respective zone. 3. Have the central data platform team manage all zones’ data assets.
• B. 1. Create one lake for each team. Inside each lake, create one zone for each domain. 2. Attach each of the BigQuery datasets created by the individual teams as assets to the respective zone. 3. Direct each domain to manage their own zone’s data assets.
• C. 1. Create one lake for each domain. Inside each lake, create one zone for each team. 2. Attach each of the BigQuery datasets created by the individual teams as assets to the respective zone. 3. Direct each domain to manage their own lake’s data assets.
• D. 1. Create one lake for each domain. Inside each lake, create one zone for each team. 2. Attach each of the BigQuery datasets created by the individual teams as assets to the respective zone. 3. Have the central data platform team manage all lakes’ data assets.

Correct answer: C

Explanation

The correct answer is C because it allows each domain to manage their own data assets, enhancing autonomy and reducing reliance on the central data platform team. This structure aligns with the principles of a data mesh, which emphasizes decentralized data ownership. The other options either maintain central control or do not properly segregate data management, which would not alleviate the bottleneck issue.