Google Professional Data Engineer exam dumps

Google Professional Data Engineer practice question 43 of 279

Professional Data Engineer. Professional level, Google Cloud. Free question with the correct answer and a full explanation.

Google Professional Data Engineer Question 43

Select 3Google Cloud Platform

Your organization is building a data pipeline that needs to operate across multiple cloud providers due to business requirements and data residency regulations. The pipeline must ensure data portability and compliance while minimizing operational complexity. Which of the following approaches will best support this scenario?

  1. A

    Use open-source tools like Apache Beam to build a unified data processing pipeline that can run on multiple cloud platforms.

  2. B

    Store all data in a single cloud provider's managed database service to simplify management.

  3. C

    Adopt containerization technologies like Kubernetes to deploy and manage applications consistently across cloud environments.

  4. D

    Implement a data format standard such as Parquet or Avro to ensure portability of data across platforms.

  5. E

    Rely on a single cloud provider's proprietary APIs for data processing to take advantage of their managed services.

Show answer and explanation

Correct answers: A, C, D

Explanation

To design a data pipeline that supports multi-cloud and data residency requirements, it is crucial to prioritize portability and avoid vendor lock-in. Using open-source tools and standard data formats ensures compatibility across cloud platforms. Containerization provides a consistent environment for application deployment, further supporting portability. Avoiding reliance on proprietary services or storing all data in a single cloud provider helps maintain flexibility and compliance.

  • A. Correct.

    Using open-source tools like Apache Beam allows you to build a data processing pipeline that is portable and can run on different cloud providers, fulfilling multi-cloud requirements.

  • B. Incorrect.

    Storing all data in a single cloud provider's managed database service would not meet the multi-cloud or data residency requirements, as it locks you into one provider.

  • C. Correct.

    Containerization technologies like Kubernetes enable consistent deployment and management of applications across multiple cloud environments, supporting portability and reducing operational complexity.

  • D. Correct.

    Using data format standards like Parquet or Avro ensures that data can be easily moved and processed across different platforms, enhancing portability and compliance.

  • E. Incorrect.

    Relying on a single cloud provider's proprietary APIs ties the solution to that provider, reducing portability and making it harder to meet multi-cloud and data residency requirements.

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