Google Professional Data Engineer exam dumps

Google Professional Data Engineer practice question 273 of 279

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

Google Professional Data Engineer Question 273

Select 3Google Cloud Platform

You are designing a data pipeline on Google Cloud for a retail company that ingests and processes real-time transaction data. The company wants to ensure resilience against data corruption and missing data during ingestion and processing. Which of the following approaches should you implement?

  1. A

    Implement Cloud Pub/Sub with dead-letter topics to capture messages that fail to process.

  2. B

    Use schema validation in Cloud Dataflow to ensure that the data adheres to the expected format before processing.

  3. C

    Configure BigQuery to automatically retry failed queries multiple times to handle transient errors.

  4. D

    Create a Cloud Storage bucket with Object Versioning enabled to retain previous versions of overwritten or deleted data.

  5. E

    Disable Cloud Logging for performance optimization to avoid capturing irrelevant logs.

Show answer and explanation

Correct answers: A, B, D

Explanation

To prepare for data corruption and missing data, it's important to implement mechanisms for detecting, capturing, and recovering from such issues. Pub/Sub dead-letter topics allow for capturing failed messages, schema validation ensures early detection of data issues, and Cloud Storage Object Versioning provides a way to recover overwritten or deleted data. These practices collectively improve the resilience of the data pipeline.

  • A. Correct.

    Correct: Cloud Pub/Sub dead-letter topics ensure that messages that fail processing due to corruption or other issues are captured for later analysis or reprocessing, improving resilience.

  • B. Correct.

    Correct: Schema validation in Cloud Dataflow ensures that malformed or missing data is flagged early in the pipeline, preventing downstream errors.

  • C. Incorrect.

    Incorrect: While retrying BigQuery queries can handle transient errors during querying, it does not address data corruption or missing data in the pipeline.

  • D. Correct.

    Correct: Enabling Object Versioning in Cloud Storage allows recovery of previous versions of files, which is helpful in case of accidental overwrites or deletions, mitigating data loss.

  • E. Incorrect.

    Incorrect: Disabling Cloud Logging may hinder debugging and auditing efforts, reducing visibility into data issues, which is counterproductive for resilience.

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