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

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

PDF
Databricks-Certified-Professional-Data-Engineer pdf
 Real Exam Questions and Answer
 Last Update: Feb 25, 2026
 Question and Answers: 195 With Explanation
 Compatible with all Devices
 Printable Format
 100% Pass Guaranteed
$25.5  $84.99
Databricks-Certified-Professional-Data-Engineer exam
PDF + Testing Engine
Databricks-Certified-Professional-Data-Engineer PDF + engine
 Both PDF & Practice Software
 Last Update: Feb 25, 2026
 Question and Answers: 195
 Discount Offer
 Download Free Demo
 24/7 Customer Support
$40.5  $134.99
Testing Engine
Databricks-Certified-Professional-Data-Engineer Engine
 Desktop Based Application
 Last Update: Feb 25, 2026
 Question and Answers: 195
 Create Multiple Test Sets
 Questions Regularly Updated
  90 Days Free Updates
  Windows and Mac Compatible
$30  $99.99
Last Week Results
32 Customers Passed Databricks
Databricks-Certified-Professional-Data-Engineer Exam
Average Score In Real Exam
86.7%
Questions came word for word from this dump
88.6%
Databricks Bundle Exams
Databricks Bundle Exams
 Duration: 3 to 12 Months
 4 Certifications
  12 Exams
 Databricks Updated Exams
 Most authenticate information
 Prepare within Days
 Time-Saving Study Content
 90 to 365 days Free Update
$249.6*
Free Databricks-Certified-Professional-Data-Engineer Exam Dumps

Verified By IT Certified Experts

CertsTopics.com Certified Safe Files

Up-To-Date Exam Study Material

99.5% High Success Pass Rate

100% Accurate Answers

Instant Downloads

Exam Questions And Answers PDF

Try Demo Before You Buy

Certification Exams with Helpful Questions And Answers

What our customers are saying

Zambia certstopics Zambia
Elias
Feb 20, 2026
Databricks victory is within reach with certstopics. Verified Q&A, real exam practice, and 24/7 support ensure success.
Pakistan certstopics Pakistan
Agneza
Jan 16, 2026
I owe my success in the Databricks-Certified-Professional-Data-Engineer exam to certstopics authentic study material and comprehensive preparation resources.
Smaller Territories of the UK certstopics Smaller Territories of the UK
Kailee
Jan 4, 2026
Certstopics PDFs for Databricks-Certified-Professional-Data-Engineer were comprehensive and easy to understand. Real exams felt like a breeze!
Sweden certstopics Sweden
Marco
Dec 18, 2025
Certstopics.com ensured my Databricks Databricks-Certified-Professional-Data-Engineer Exam readiness. Their comprehensive resources covered all the bases.

Databricks Certified Data Engineer Professional Exam Questions and Answers

Question 1

A production workload incrementally applies updates from an external Change Data Capture feed to a Delta Lake table as an always-on Structured Stream job. When data was initially migrated for this table, OPTIMIZE was executed and most data files were resized to 1 GB. Auto Optimize and Auto Compaction were both turned on for the streaming production job. Recent review of data files shows that most data files are under 64 MB, although each partition in the table contains at least 1 GB of data and the total table size is over 10 TB.

Which of the following likely explains these smaller file sizes?

Options:

A.

Databricks has autotuned to a smaller target file size to reduce duration of MERGE operations

B.

Z-order indices calculated on the table are preventing file compaction

C Bloom filler indices calculated on the table are preventing file compaction

C.

Databricks has autotuned to a smaller target file size based on the overall size of data in the table

D.

Databricks has autotuned to a smaller target file size based on the amount of data in each partition

Buy Now
Question 2

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.

Question 3

The following code has been migrated to a Databricks notebook from a legacy workload:

The code executes successfully and provides the logically correct results, however, it takes over 20 minutes to extract and load around 1 GB of data.

Which statement is a possible explanation for this behavior?

Options:

A.

%sh triggers a cluster restart to collect and install Git. Most of the latency is related to cluster startup time.

B.

Instead of cloning, the code should use %sh pip install so that the Python code can get executed in parallel across all nodes in a cluster.

C.

%sh does not distribute file moving operations; the final line of code should be updated to use %fs instead.

D.

Python will always execute slower than Scala on Databricks. The run.py script should be refactored to Scala.

E.

%sh executes shell code on the driver node. The code does not take advantage of the worker nodes or Databricks optimized Spark.