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Databricks Databricks-Certified-Professional-Data-Engineer Dumps

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Databricks-Certified-Professional-Data-Engineer
Exam Name:
Databricks Certified Data Engineer Professional Exam
Last Update: Oct 15, 2025
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The Databricks Data Engineer exam evaluates key skills such as data processing, building data pipelines, performance optimization, and working with big data using Apache Spark and the Databricks platform, emphasizing both conceptual understanding and practical application in data engineering.

The minimum passing score for the Databricks-Certified-Professional-Data-Engineer Exam is typically set at 70%, although this benchmark may vary slightly based on exam versions and the complexity of the questions presented in the specific test iteration.

The Databricks-Certified-Professional-Data-Engineer Exam primarily features multiple-choice and multiple-response questions, designed to assess a candidate's practical and theoretical knowledge in data engineering, particularly focusing on scenarios and problem-solving using the Databricks and Apache Spark platform.

Obtaining the Databricks-Certified-Professional-Data-Engineer certification significantly boosts a data engineering career by validating expertise in big data processing and analytics on Databricks and Apache Spark, enhancing job prospects, and positioning the individual as a skilled professional in a rapidly growing field.

The Databricks Certified Professional Data Engineer Exam assesses an individual's ability to perform advanced data engineering tasks using Databricks. This includes knowledge of Databricks platform, Apache Spark™, Delta Lake, MLflow, Databricks CLI, and REST API?.

The exam consists of 60 multiple-choice questions that must be completed in 120 minutes. The exam covers topics such as Databricks tooling, data processing, data modeling, security and governance, monitoring and logging, and testing and deployment. The registration fee for the exam is $200?.

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Databricks Certified Data Engineer Professional Exam Questions and Answers

Questions 1

Spill occurs as a result of executing various wide transformations. However, diagnosing spill requires one to proactively look for key indicators.

Where in the Spark UI are two of the primary indicators that a partition is spilling to disk?

Options:

A.

Stage’s detail screen and Executor’s files

B.

Stage’s detail screen and Query’s detail screen

C.

Driver’s and Executor’s log files

D.

Executor’s detail screen and Executor’s log files

Questions 2

A CHECK constraint has been successfully added to the Delta table named activity_details using the following logic:

A batch job is attempting to insert new records to the table, including a record where latitude = 45.50 and longitude = 212.67.

Which statement describes the outcome of this batch insert?

Options:

A.

The write will fail when the violating record is reached; any records previously processed will be recorded to the target table.

B.

The write will fail completely because of the constraint violation and no records will be inserted into the target table.

C.

The write will insert all records except those that violate the table constraints; the violating records will be recorded to a quarantine table.

D.

The write will include all records in the target table; any violations will be indicated in the boolean column named valid_coordinates.

E.

The write will insert all records except those that violate the table constraints; the violating records will be reported in a warning log.

Questions 3

Two of the most common data locations on Databricks are the DBFS root storage and external object storage mounted with dbutils.fs.mount().

Which of the following statements is correct?

Options:

A.

DBFS is a file system protocol that allows users to interact with files stored in object storage using syntax and guarantees similar to Unix file systems.

B.

By default, both the DBFS root and mounted data sources are only accessible to workspace administrators.

C.

The DBFS root is the most secure location to store data, because mounted storage volumes must have full public read and write permissions.

D.

Neither the DBFS root nor mounted storage can be accessed when using %sh in a Databricks notebook.

E.

The DBFS root stores files in ephemeral block volumes attached to the driver, while mounted directories will always persist saved data to external storage between sessions.

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