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Databricks-Certified-Data-Engineer-Associate Exam Dumps : Databricks Certified Data Engineer Associate Exam

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Databricks Certified Data Engineer Associate Exam Questions and Answers

Question 1

A data analysis team has noticed that their Databricks SQL queries are running too slowly when connected to their always-on SQL endpoint. They claim that this issue is present when many members of the team are running small queries simultaneously. They ask the data engineering team for help. The data engineering team notices that each of the team’s queries uses the same SQL endpoint.

Which of the following approaches can the data engineering team use to improve the latency of the team’s queries?

Options:

A.

They can increase the cluster size of the SQL endpoint.

B.

They can increase the maximum bound of the SQL endpoint’s scaling range.

C.

They can turn on the Auto Stop feature for the SQL endpoint.

D.

They can turn on the Serverless feature for the SQL endpoint.

E.

They can turn on the Serverless feature for the SQL endpoint and change the Spot Instance Policy to “Reliability Optimized.”

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Question 2

The Delta transaction log for the ‘students’ tables is shown using the ‘DESCRIBE HISTORY students’ command. A Data Engineer needs to query the table as it existed before the UPDATE operation listed in the log.

Which command should the Data Engineer use to achieve this? (Choose two.)

Options:

A.

SELECT * FROM students@v4

B.

SELECT * FROM students TIMESTAMP AS OF ‘2024-04-22T 14:32:47.000+00:00’

C.

SELECT * FROM students FROM HISTORY VERSION AS OF 3

D.

SELECT * FROM students VERSION AS OF 5

E.

SELECT * FROM students TIMESTAMP AS OF ‘2024-04-22T 14:32:58.000+00:00’

Question 3

A data engineering team ingests customer transaction data from three enterprise sources: a SQL database, Amazon S3, and an Apache Kafka stream. The data must maintain lineage and support compliance audits that require access to historical snapshots.

Which Lakeflow Connect configuration satisfies both the governance and audit requirements?

Options:

A.

Use a single connector with batch scheduling, a shared Unity Catalog schema, and incremental snapshots stored externally.

B.

Use a single Lakeflow connector for all three sources, write directly to Delta tables, and disable table versioning to reduce storage costs.

C.

Use separate connectors with full-load synchronization only, archive historical data separately, and create external tables for audit queries.

D.

Use separate connectors for each source, source-appropriate incremental processing, individual Unity Catalog schemas, and retained Delta table versions for audit compliance.