Databricks Data Engineer Professional exam dumps

Databricks Data Engineer Professional practice question 253 of 313

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

Databricks Data Engineer Professional Question 253

Select 4

You are tasked with deploying a new version of a data pipeline in a Databricks environment. Before deployment, you want to ensure that the pipeline functions correctly and does not disrupt existing processes. Which steps should you include in your deployment process to ensure a smooth deployment?

  1. A

    Perform unit tests on individual components of the pipeline.

  2. B

    Directly deploy the pipeline in production without testing to minimize delays.

  3. C

    Use a staging environment to validate the full pipeline with representative data.

  4. D

    Rollback the changes immediately after deployment, regardless of the outcome.

  5. E

    Implement integration tests to validate interactions between pipeline components.

  6. F

    Monitor the production environment for errors after deployment.

Show answer and explanation

Correct answers: A, C, E, F

Explanation

A robust deployment process includes thorough testing at multiple levels (unit, integration, and end-to-end), validation in a staging environment, and monitoring the production environment post-deployment. These steps ensure that the pipeline functions correctly while minimizing risks and disruptions. Directly deploying without testing or rolling back changes unnecessarily can lead to inefficiencies and potential system failures.

  • A. Correct.

    Unit testing ensures that individual components of the pipeline work as expected, which is a critical step in identifying issues early in the process.

  • B. Incorrect.

    Skipping testing and deploying directly to production can lead to unexpected errors and disruptions, so this is not a recommended approach.

  • C. Correct.

    Using a staging environment allows you to validate the entire pipeline in a controlled setting before moving to production, reducing the risk of failure.

  • D. Incorrect.

    Rolling back changes immediately without assessing the outcome is unnecessary unless there are critical issues identified post-deployment.

  • E. Correct.

    Integration testing ensures that different components of the pipeline work together as expected, which is essential for complex workflows.

  • F. Correct.

    Monitoring the production environment after deployment helps detect issues that might not have been caught during testing, ensuring quick resolution if problems arise.

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