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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A data engineering team has two tables. The first table march_transactions is a collection of all retail transactions in the month of March. The second table april_transactions is a collection of all retail transactions in the month of April. There are no duplicate records between the tables.
Which of the following commands should be run to create a new table all_transactions that contains all records from march_transactions and april_transactions without duplicate records?

• A.CREATE TABLE all_transactions AS
  SELECT * FROM march_transactions
  INNER JOIN SELECT * FROM april_transactions;
• B.CREATE TABLE all_transactions AS
  SELECT * FROM march_transactions
  UNION SELECT * FROM april_transactions;
• C.CREATE TABLE all_transactions AS
  SELECT * FROM march_transactions
  OUTER JOIN SELECT * FROM april_transactions;
• D.CREATE TABLE all_transactions AS
  SELECT * FROM march_transactions
  INTERSECT SELECT * from april_transactions;
• E.CREATE TABLE all_transactions AS
  SELECT * FROM march_transactions
  MERGE SELECT * FROM april_transactions;

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Which of the following SQL keywords can be used to convert a table from a long format to a wide format?

• A.PIVOT
• B.CONVERT
• C.WHERE
• D.TRANSFORM
• E.SUM

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A data engineer wants to create a reproducible ETL workflow that runs every night and executes multiple notebooks in sequence. The workflow should retry failed tasks and provide monitoring capabilities. Which Databricks feature is best suited for this requirement?

• A.Databricks Jobs
• B.MLflow
• C.Delta Lake
• D.DBFS

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A data engineer is working with a very large dataset and wants to improve query performance by colocating related data in the same files. The engineer decides to apply Z-ordering on frequently filtered columns. Which Delta Lake command is used?

• A.ANALYZE TABLE
• B.OPTIMIZE ZORDER BY
• C.CACHE TABLE
• D.VACUUM ZORDER

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