Databricks Machine Learning Associate exam dumps

Databricks Machine Learning Associate practice question 422 of 656

Databricks Certified Machine Learning Associate. Associate level, Databricks. Free question with the correct answer and a full explanation.

Databricks Machine Learning Associate Question 422

Select 3

A data engineering team wants to create a feature store table in Unity Catalog to be shared across multiple Databricks workspaces in their organization. What are the benefits of creating this feature store table at the account level in Unity Catalog instead of at the workspace level?

  1. A

    Feature store tables at the account level enable seamless sharing of features across multiple workspaces.

  2. B

    Account-level feature store tables allow for centralized governance and access control policies to be applied consistently across all workspaces.

  3. C

    Creating feature store tables at the account level improves the training performance of machine learning models.

  4. D

    Account-level feature store tables eliminate the need for data replication across workspaces, reducing storage duplication.

  5. E

    Using account-level feature store tables ensures that individual workspaces are isolated from each other, improving security.

Show answer and explanation

Correct answers: A, B, D

Explanation

Creating feature store tables at the account level in Unity Catalog provides significant benefits, such as seamless sharing of features across workspaces, centralized governance, and reduced storage duplication. These advantages help organizations manage and use their data more efficiently across multiple Databricks workspaces.

  • A. Correct.

    This is correct. Feature store tables at the account level allow sharing features across multiple workspaces without needing separate copies for each workspace.

  • B. Correct.

    This is correct. By creating feature store tables at the account level, governance and access control can be centrally managed using Unity Catalog, ensuring consistent permissions across workspaces.

  • C. Incorrect.

    This is incorrect. The location of the feature store table (account-level vs. workspace-level) does not directly impact the training performance of machine learning models.

  • D. Correct.

    This is correct. Account-level feature store tables reduce the need to replicate data in each workspace, which helps minimize storage costs and duplication.

  • E. Incorrect.

    This is incorrect. While account-level feature store tables enable centralized access control, they do not isolate individual workspaces. Instead, they facilitate sharing and collaboration between workspaces.

Timed practice exam

Take a Databricks Machine Learning Associate practice test under exam conditions

48 questions in 90 minutes, drawn from this bank, with a score report and a per-question review when you finish.

Start timed exam