New Year Sale 70% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: save70

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:
Vendor:
Questions:
195
Last Updated:
Jan 7, 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

Are you worried about passing the Databricks Databricks-Certified-Professional-Data-Engineer (Databricks Certified Data Engineer Professional Exam) exam? Download the most recent Databricks Databricks-Certified-Professional-Data-Engineer braindumps with answers that are 100% real. After downloading the Databricks Databricks-Certified-Professional-Data-Engineer exam dumps training , you can receive 99 days of free updates, making this website one of the best options to save additional money. In order to help you prepare for the Databricks Databricks-Certified-Professional-Data-Engineer exam questions and verified answers by IT certified experts, CertsTopics has put together a complete collection of dumps questions and answers. To help you prepare and pass the Databricks Databricks-Certified-Professional-Data-Engineer exam on your first attempt, we have compiled actual exam questions and their answers. 

Our (Databricks Certified Data Engineer Professional Exam) Study Materials are designed to meet the needs of thousands of candidates globally. A free sample of the CompTIA Databricks-Certified-Professional-Data-Engineer test is available at CertsTopics. Before purchasing it, you can also see the Databricks Databricks-Certified-Professional-Data-Engineer practice exam demo.

Databricks Certified Data Engineer Professional Exam Questions and Answers

Question 1

To reduce storage and compute costs, the data engineering team has been tasked with curating a series of aggregate tables leveraged by business intelligence dashboards, customer-facing applications, production machine learning models, and ad hoc analytical queries.

The data engineering team has been made aware of new requirements from a customer-facing application, which is the only downstream workload they manage entirely. As a result, an aggregate table used by numerous teams across the organization will need to have a number of fields renamed, and additional fields will also be added.

Which of the solutions addresses the situation while minimally interrupting other teams in the organization without increasing the number of tables that need to be managed?

Options:

A.

Send all users notice that the schema for the table will be changing; include in the communication the logic necessary to revert the new table schema to match historic queries.

B.

Configure a new table with all the requisite fields and new names and use this as the source for the customer-facing application; create a view that maintains the original data schema and table name by aliasing select fields from the new table.

C.

Create a new table with the required schema and new fields and use Delta Lake's deep clone functionality to sync up changes committed to one table to the corresponding table.

D.

Replace the current table definition with a logical view defined with the query logic currently writing the aggregate table; create a new table to power the customer-facing application.

E.

Add a table comment warning all users that the table schema and field names will be changing on a given date; overwrite the table in place to the specifications of the customer-facing application.

Buy Now
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 data engineer wants to join a stream of advertisement impressions (when an ad was shown) with another stream of user clicks on advertisements to correlate when impression led to monitizable clicks.

Which solution would improve the performance?

A)

B)

C)

D)

Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D