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

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Databricks Certified Data Engineer Professional Exam Questions and Answers

Question 1

Which statement describes integration testing?

Options:

A.

Validates interactions between subsystems of your application

B.

Requires an automated testing framework

C.

Requires manual intervention

D.

Validates an application use case

E.

Validates behavior of individual elements of your application

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Question 2

All records from an Apache Kafka producer are being ingested into a single Delta Lake table with the following schema:

key BINARY, value BINARY, topic STRING, partition LONG, offset LONG, timestamp LONG

There are 5 unique topics being ingested. Only the "registration" topic contains Personal Identifiable Information (PII). The company wishes to restrict access to PII. The company also wishes to only retain records containing PII in this table for 14 days after initial ingestion. However, for non-PII information, it would like to retain these records indefinitely.

Which of the following solutions meets the requirements?

Options:

A.

All data should be deleted biweekly; Delta Lake's time travel functionality should be leveraged to maintain a history of non-PII information.

B.

Data should be partitioned by the registration field, allowing ACLs and delete statements to be set for the PII directory.

C.

Because the value field is stored as binary data, this information is not considered PII and no special precautions should be taken.

D.

Separate object storage containers should be specified based on the partition field, allowing isolation at the storage level.

E.

Data should be partitioned by the topic field, allowing ACLs and delete statements to leverage partition boundaries.

Question 3

A DLT pipeline includes the following streaming tables:

Raw_lot ingest raw device measurement data from a heart rate tracking device.

Bgm_stats incrementally computes user statistics based on BPM measurements from raw_lot.

How can the data engineer configure this pipeline to be able to retain manually deleted or updated records in the raw_iot table while recomputing the downstream table when a pipeline update is run?

Options:

A.

Set the skipChangeCommits flag to true on bpm_stats

B.

Set the SkipChangeCommits flag to true raw_lot

C.

Set the pipelines, reset, allowed property to false on bpm_stats

D.

Set the pipelines, reset, allowed property to false on raw_iot