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?

• 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.

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While investigating a data issue in a Delta table, you wanted to review logs to see when and who updated the table, what is the best way to review this data?

• A.Review event logs in the Workspace
• B.Run SQL SHOW HISTORY table_name
• C.Check Databricks SQL Audit logs
• D.Run SQL command DESCRIBE HISTORY table_name
• E.Review workspace audit logs

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Two data engineers are working on the same Databricks notebook in separate branches. Both have edited the same section of code. When one tries to merge the other's branch into their own using the Databricks Git folders UI, a merge conflict occurs on that notebook file. The UI highlights the conflict and presents options for resolution.
How should the data engineers resolve this merge conflict using Databricks Git folders?

• A.Abort the merge, discard all local changes, and try the merge operation again without reviewing the conflicting code.
• B.Delete the conflicted notebook file via the Databricks workspace UI, commit the deletion, and recreate the notebook from scratch in a new commit to bypass the conflict entirely.
• C.Use the Git CLI in the cluster's web terminal to force-push the conflicted merge (git push -force), overriding the remote branch with the local version and discarding changes.
• D.Use the Git folders UI to manually edit the notebook file, selecting the desired lines from both versions and removing the conflict markers, then mark the conflict as resolved.

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In order to facilitate near real-time workloads, a data engineer is creating a helper function to leverage the schema detection and evolution functionality of Databricks Auto Loader. The desired function will automatically detect the schema of the source directly, incrementally process JSON files as they arrive in a source directory, and automatically evolve the schema of the table when new fields are detected.
The function is displayed below with a blank:
Which response correctly fills in the blank to meet the specified requirements?

• A.Option A
• B.Option B
• C.Option C
• D.Option D
• E.Option E

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A Delta Lake table was created with the below query:
Consider the following query:
DROP TABLE prod.sales_by_store -
If this statement is executed by a workspace admin, which result will occur?

• A.Nothing will occur until a COMMIT command is executed.
• B.The table will be removed from the catalog but the data will remain in storage.
• C.The table will be removed from the catalog and the data will be deleted.
• D.An error will occur because Delta Lake prevents the deletion of production data.
• E.Data will be marked as deleted but still recoverable with Time Travel.

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