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Databricks Databricks-Certified-Professional-Data-Engineer Exam With Confidence Using Practice Dumps

Exam Code:
Databricks-Certified-Professional-Data-Engineer
Exam Name:
Databricks Certified Data Engineer Professional Exam
Certification:
Databricks Certification
Vendor:
Databricks
Questions:
195
Last Updated:
Mar 2, 2026
Exam Status:
Stable
Databricks Databricks-Certified-Professional-Data-Engineer

Databricks-Certified-Professional-Data-Engineer: Databricks Certification Exam 2025 Study Guide Pdf and Test Engine

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Databricks Certified Data Engineer Professional Exam Questions and Answers

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Question 1

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.

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Question 2

A Databricks SQL dashboard has been configured to monitor the total number of records present in a collection of Delta Lake tables using the following query pattern:

SELECT COUNT (*) FROM table -

Which of the following describes how results are generated each time the dashboard is updated?

Options:

A.

The total count of rows is calculated by scanning all data files

B.

The total count of rows will be returned from cached results unless REFRESH is run

C.

The total count of records is calculated from the Delta transaction logs

D.

The total count of records is calculated from the parquet file metadata

E.

The total count of records is calculated from the Hive metastore

Question 3

A junior member of the data engineering team is exploring the language interoperability of Databricks notebooks. The intended outcome of the below code is to register a view of all sales that occurred in countries on the continent of Africa that appear in the geo_lookup table.

Before executing the code, running SHOW TABLES on the current database indicates the database contains only two tables: geo_lookup and sales.

Which statement correctly describes the outcome of executing these command cells in order in an interactive notebook?

Options:

A.

Both commands will succeed. Executing show tables will show that countries at and sales at have been registered as views.

B.

Cmd 1 will succeed. Cmd 2 will search all accessible databases for a table or view named countries af: if this entity exists, Cmd 2 will succeed.

C.

Cmd 1 will succeed and Cmd 2 will fail, countries at will be a Python variable representing a PySpark DataFrame.

D.

Both commands will fail. No new variables, tables, or views will be created.

E.

Cmd 1 will succeed and Cmd 2 will fail, countries at will be a Python variable containing a list of strings.

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