A platform engineer is creating catalogs and schemas for the development team to use.
The engineer has created an initial catalog, catalog_A, and initial schema, schema_A. The engineer has also granted USE CATALOG, USE SCHEMA, and CREATE TABLE to the development team so that the engineer can begin populating the schema with new tables.
Despite being owner of the catalog and schema, the engineer noticed that they do not have access to the underlying tables in Schema_A.
What explains the engineer's lack of access to the underlying tables?

• A. Permissions explicitly given by the table creator are the only way the Platform Engineer could access the underlying tables in their schema.
• B. The platform engineer needs to execute a REFRESH statement as the table permissions did not automatically update for owners.
• C. The owner of the schema does not automatically have permission to tables within the schema, but can grant them to themselves at any point.
• D. Users granted with USE CATALOG can modify the owner's permissions to downstream tables.

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In order to prevent accidental commits to production data, a senior data engineer has instituted a policy that all development work will reference clones of Delta Lake tables. After testing both deep and shallow clone, development tables are created using shallow clone. A few weeks after initial table creation, the cloned versions of several tables implemented as Type 1 Slowly Changing Dimension (SCD) stop working. The transaction logs for the source tables show that vacuum was run the day before.
Why are the cloned tables no longer working?

• A. The data files compacted by vacuum are not tracked by the cloned metadata; running refresh on the cloned table will pull in recent changes.
• B. Because Type 1 changes overwrite existing records, Delta Lake cannot guarantee data consistency for cloned tables.
• C. Tables created with SHALLOW CLONE are automatically deleted after their default retention threshold of 7 days.
• D. The metadata created by the clone operation is referencing data files that were purged as invalid by the vacuum command
• E. Running vacuum automatically invalidates any shallow clones of a table; deep clone should always be used when a cloned table will be repeatedly queried.

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

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The data governance team is reviewing code used for deleting records for compliance with GDPR. They note the following logic is used to delete records from the Delta Lake table named users.

Assuming that user_id is a unique identifying key and that delete_requests contains all users that have requested deletion, which statement describes whether successfully executing the above logic guarantees that the records to be deleted are no longer accessible and why?

• A. No; the Delta cache may return records from previous versions of the table until the cluster is restarted.
• B. No; the Delta Lake delete command only provides ACID guarantees when combined with the merge into command.
• C. Yes; Delta Lake ACID guarantees provide assurance that the delete command succeeded fully and permanently purged these records.
• D. Yes; the Delta cache immediately updates to reflect the latest data files recorded to disk.
• E. No; files containing deleted records may still be accessible with time travel until a vacuum command is used to remove invalidated data files.

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Which statement describes the default execution mode for Databricks Auto Loader?

• A. Cloud vendor-specific queue storage and notification services are configured to track newly arriving files; new files are incrementally and impotently into the target Delta Lake table.
• B. Cloud vendor-specific queue storage and notification services are configured to track newly arriving files; the target table is materialized by directly querying all valid files in the source directory.
• C. Webhook trigger Databricks job to run anytime new data arrives in a source directory; new data automatically merged into target tables using rules inferred from the data.
• D. New files are identified by listing the input directory; new files are incrementally and idempotently loaded into the target Delta Lake table.
• E. New files are identified by listing the input directory; the target table is materialized by directory querying all valid files in the source directory.

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