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Databricks-Certified-Professional-Data-Engineer Exam Dumps : Databricks Certified Data Engineer Professional Exam

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Databricks Certified Data Engineer Professional Exam Questions and Answers

Question 1

The DevOps team has configured a production workload as a collection of notebooks scheduled to run daily using the Jobs UI. A new data engineering hire is onboarding to the team and has requested access to one of these notebooks to review the production logic.

What are the maximum notebook permissions that can be granted to the user without allowing accidental changes to production code or data?

Options:

A.

Can Manage

B.

Can Edit

C.

No permissions

D.

Can Read

E.

Can Run

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Question 2

The data engineer team is configuring environment for development testing, and production before beginning migration on a new data pipeline. The team requires extensive testing on both the code and data resulting from code execution, and the team want to develop and test against similar production data as possible.

A junior data engineer suggests that production data can be mounted to the development testing environments, allowing pre production code to execute against production data. Because all users have

Admin privileges in the development environment, the junior data engineer has offered to configure permissions and mount this data for the team.

Which statement captures best practices for this situation?

Options:

A.

Because access to production data will always be verified using passthrough credentials it is safe to mount data to any Databricks development environment.

B.

All developer, testing and production code and data should exist in a single unified workspace; creating separate environments for testing and development further reduces risks.

C.

In environments where interactive code will be executed, production data should only be accessible with read permissions; creating isolated databases for each environment further reduces risks.

D.

Because delta Lake versions all data and supports time travel, it is not possible for user error or malicious actors to permanently delete production data, as such it is generally safe to mount production data anywhere.

Question 3

The marketing team is looking to share data in an aggregate table with the sales organization, but the field names used by the teams do not match, and a number of marketing specific fields have not been approval for the sales org.

Which of the following solutions addresses the situation while emphasizing simplicity?

Options:

A.

Create a view on the marketing table selecting only these fields approved for the sales team alias the names of any fields that should be standardized to the sales naming conventions.

B.

Use a CTAS statement to create a derivative table from the marketing table configure a production jon to propagation changes.

C.

Add a parallel table write to the current production pipeline, updating a new sales table that varies as required from marketing table.

D.

Create a new table with the required schema and use Delta Lake's DEEP CLONE functionality to sync up changes committed to one table to the corresponding table.