A data engineer has three tables in a Delta Live Tables (DLT) pipeline. They have configured the pipeline to drop invalid records at each table. They notice that some data is being dropped due to quality concerns at some point in the DLT pipeline. They would like to determine at which table in their pipeline the data is being dropped.
Which of the following approaches can the data engineer take to identify the table that is dropping the records?

• A.They can navigate to the DLT pipeline page, click on each table, and view the data quality statistics.
• B.They can set up DLT to notify them via email when records are dropped.
• C.They cannot determine which table is dropping the records.
• D.They can navigate to the DLT pipeline page, click on the "Error" button, and review the present errors.
• E.They can set up separate expectations for each table when developing their DLT pipeline.

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A dataset has been defined using Delta Live Tables and includes an expectations clause:
CONSTRAINT valid_timestamp EXPECT (timestamp > '2020-01-01') ON VIOLATION DROP ROW What is the expected behavior when a batch of data containing data that violates these constraints is processed?

• A.Records that violate the expectation are dropped from the target dataset and loaded into a quarantine table.
• B.Records that violate the expectation are added to the target dataset and flagged as invalid in a field added to the target dataset.
• C.Records that violate the expectation are dropped from the target dataset and recorded as invalid in the event log.
• D.Records that violate the expectation are added to the target dataset and recorded as invalid in the event log.
• E.Records that violate the expectation cause the job to fail.

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A data engineer and data analyst are working together on a data pipeline. The data engineer is working on the raw, bronze, and silver layers of the pipeline using Python, and the data analyst is working on the gold layer of the pipeline using SQL. The raw source of the pipeline is a streaming input. They now want to migrate their pipeline to use Delta Live Tables.
Which of the following changes will need to be made to the pipeline when migrating to Delta Live Tables?

• A.None of these changes will need to be made
• B.The pipeline will need to stop using the medallion-based multi-hop architecture
• C.The pipeline will need to be written entirely in SQL
• D.The pipeline will need to use a batch source in place of a streaming source
• E.The pipeline will need to be written entirely in Python

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Which of the following is a benefit of the Databricks Lakehouse Platform embracing open source technologies?

• A.Cloud-specific integrations
• B.Simplified governance
• C.Ability to scale storage
• D.Ability to scale workloads
• E.Avoiding vendor lock-in

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A data engineer has realized that they made a mistake when making a daily update to a table. They need to use Delta time travel to restore the table to a version that is 3 days old. However, when the data engineer attempts to time travel to the older version, they are unable to restore the data because the data files have been deleted.
Which of the following explains why the data files are no longer present?

• A.The HISTORY command was run on the table
• B.The TIME TRAVEL command was run on the table
• C.The DELETE HISTORY command was run on the table
• D.The OPTIMIZE command was nun on the table
• E.The VACUUM command was run on the table

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