Google Professional Data Engineer Question 166
Select 3Google Cloud PlatformYour organization is adopting a data mesh architecture to decentralize data ownership and enable domain teams to manage their data products. As a Professional Data Engineer, you need to ensure that the design facilitates self-serve data infrastructure for the teams. Which considerations are crucial for designing an effective data mesh?
- A
Implementing strong governance policies to ensure data security and compliance across domains.
- B
Enforcing a centralized data platform where all domain teams store their data to maintain consistency.
- C
Providing domain teams with tools and platforms that enable them to develop, deploy, and manage their own data products.
- D
Designing data products with APIs and discoverability to facilitate data sharing across domains.
- E
Mandating that all data processing pipelines be approved by a central data engineering team.
Show answer and explanation
Correct answers: A, C, D
Explanation
In a data mesh architecture, decentralization of data ownership and enabling domain autonomy are key principles. This requires strong governance to ensure security and compliance, self-serve infrastructure to empower domain teams to manage their own data products, and interoperability through APIs and discoverability for cross-domain data sharing. Centralized control mechanisms, such as a centralized platform or approval processes, go against the goals of a data mesh.
- A. Correct.
Strong governance policies are crucial in a data mesh to ensure data security, compliance, and consistency across decentralized domains.
- B. Incorrect.
A centralized data platform contradicts the principles of a data mesh, which aims to decentralize data ownership and promote domain autonomy.
- C. Correct.
Providing domain teams with self-serve tools and platforms is essential for enabling them to independently manage their data products in a data mesh architecture.
- D. Correct.
Designing discoverable data products with APIs facilitates data sharing and collaboration between domains, aligning with the data mesh principles.
- E. Incorrect.
Requiring central approval for all data processing pipelines conflicts with the autonomy of domain teams, which is a key principle of the data mesh approach.