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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A data engineering team has noticed that their Databricks SQL queries are running too slowly when they are submitted to a non-running SQL endpoint. The data engineering team wants this issue to be resolved.
Which of the following approaches can the team use to reduce the time it takes to return results in this scenario?

• A.They can turn on the Serverless feature for the SQL endpoint and change the Spot Instance Policy to
  "Reliability Optimized."
• B.They can turn on the Auto Stop feature for the SQL endpoint.
• C.They can increase the cluster size of the SQL endpoint.
• D.They can turn on the Serverless feature for the SQL endpoint.
• E.They can increase the maximum bound of the SQL endpoint's scaling range

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In order for Structured Streaming to reliably track the exact progress of the processing so that it can handle any kind of failure by restarting and/or reprocessing, which of the following two approaches is used by Spark to record the offset range of the data being processed in each trigger?

• A.Checkpointing and Write-ahead Logs
• B.Structured Streaming cannot record the offset range of the data being processed in each trigger.
• C.Replayable Sources and Idempotent Sinks
• D.Write-ahead Logs and Idempotent Sinks
• E.Checkpointing and Idempotent Sinks

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A data engineer has been using a Databricks SQL dashboard to monitor the cleanliness of the input data to a data analytics dashboard for a retail use case. The job has a Databricks SQL query that returns the number of store-level records where sales is equal to zero. The data engineer wants their entire team to be notified via a messaging webhook whenever this value is greater than 0.
Which of the following approaches can the data engineer use to notify their entire team via a messaging webhook whenever the number of stores with $0 in sales is greater than zero?

• A.They can set up an Alert with a new webhook alert destination.
• B.They can set up an Alert with a custom template.
• C.They can set up an Alert with one-time notifications.
• D.They can set up an Alert with a new email alert destination.
• E.They can set up an Alert without notifications.

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A data engineer needs to create a table in Databricks using data from a CSV file at location /path/to/csv.
They run the following command:

Which of the following lines of code fills in the above blank to successfully complete the task?

• A.FROM "path/to/csv"
• B.FROM CSV
• C.USING DELTA
• D.USING CSV
• E.None of these lines of code are needed to successfully complete the task

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