QUIZ 2025 DATABRICKS-CERTIFIED-PROFESSIONAL-DATA-ENGINEER: PERFECT STANDARD DATABRICKS CERTIFIED PROFESSIONAL DATA ENGINEER EXAM ANSWERS

Quiz 2025 Databricks-Certified-Professional-Data-Engineer: Perfect Standard Databricks Certified Professional Data Engineer Exam Answers

Quiz 2025 Databricks-Certified-Professional-Data-Engineer: Perfect Standard Databricks Certified Professional Data Engineer Exam Answers

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When preparing to take the Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer) exam dumps, knowing where to start can be a little frustrating, but with TestBraindump Databricks Databricks-Certified-Professional-Data-Engineer practice questions, you will feel fully prepared. Using our Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer) practice test software, you can prepare for the increased difficulty on Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer) exam day. Plus, we have various question types and difficulty levels so that you can tailor your Databricks Certified Professional Data Engineer Exam (Databricks-Certified-Professional-Data-Engineer) exam dumps preparation to your requirements.

Databricks Certified Professional Data Engineer certification is designed for data engineers who are responsible for building and maintaining data pipelines and data lakes on the Databricks platform. Databricks Certified Professional Data Engineer Exam certification exam covers a wide range of topics, including data engineering concepts, data modeling, data ingestion, data transformation, data processing, and data warehousing. Databricks-Certified-Professional-Data-Engineer Exam is designed to assess a candidate's ability to design, build, and maintain scalable and reliable data pipelines on the Databricks platform.

>> Standard Databricks-Certified-Professional-Data-Engineer Answers <<

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Databricks is a leading company in the field of data engineering and machine learning. The company offers a wide range of services and tools to help organizations manage and analyze their data more effectively. One of the key offerings from Databricks is the Databricks Certified Professional Data Engineer (Databricks-Certified-Professional-Data-Engineer) certification exam. Databricks-Certified-Professional-Data-Engineer Exam is designed to test the skills and knowledge of data engineers who work with Databricks.

Databricks Certified Professional Data Engineer Exam Sample Questions (Q40-Q45):

NEW QUESTION # 40
A nightly job ingests data into a Delta Lake table using the following code:

The next step in the pipeline requires a function that returns an object that can be used to manipulate new records that have not yet been processed to the next table in the pipeline.
Which code snippet completes this function definition?
def new_records():

  • A. return spark.readStream.load("bronze")
  • B. return spark.read.option("readChangeFeed", "true").table ("bronze")
  • C. return spark.readStream.table("bronze")
  • D.

Answer: D

Explanation:
Explanation
This is the correct answer because it completes the function definition that returns an object that can be used to manipulate new records that have not yet been processed to the next table in the pipeline. The object returned by this function is a DataFrame that contains all change events from a Delta Lake table that has enabled change data feed. The readChangeFeed option is set to true to indicate that the DataFrame should read changes from the table, and the table argument specifies the name of the table to read changes from. The DataFrame will have a schema that includes four columns: operation, partition, value, and timestamp. The operation column indicates the type of change event, such as insert, update, or delete. The partition column indicates the partition where the change event occurred. The value column contains the actual data of the change event as a struct type. The timestamp column indicates the time when the change event was committed. Verified References: [Databricks Certified Data Engineer Professional], under "Delta Lake" section; Databricks Documentation, under "Read changes in batch queries" section.


NEW QUESTION # 41
The security team is exploring whether or not the Databricks secrets module can be leveraged for connecting to an external database.
After testing the code with all Python variables being defined with strings, they upload the password to the secrets module and configure the correct permissions for the currently active user. They then modify their code to the following (leaving all other variables unchanged).

Which statement describes what will happen when the above code is executed?

  • A. An interactive input box will appear in the notebook; if the right password is provided, the connection will succeed and the password will be printed in plain text.
  • B. An interactive input box will appear in the notebook; if the right password is provided, the connection will succeed and the encoded password will be saved to DBFS.
  • C. The connection to the external table will fail; the string "redacted" will be printed.
  • D. The connection to the external table will succeed; the string value of password will be printed in plain text.
  • E. The connection to the external table will succeed; the string "redacted" will be printed.

Answer: E

Explanation:
This is the correct answer because the code is using the dbutils.secrets.get method to retrieve the password from the secrets module and store it in a variable. The secrets module allows users to securely store and access sensitive information such as passwords, tokens, or API keys. The connection to the external table will succeed because the password variable will contain the actual password value. However, when printing the password variable, the string "redacted" will be displayed instead of the plain text password, as a security measure to prevent exposing sensitive information in notebooks. Verified References: [Databricks Certified Data Engineer Professional], under "Security & Governance" section; Databricks Documentation, under
"Secrets" section.


NEW QUESTION # 42
Two junior data engineers are authoring separate parts of a single data pipeline notebook. They are working on
separate Git branches so they can pair program on the same notebook simultaneously. A senior data engineer
experienced in Databricks suggests there is a better alternative for this type of collaboration.
Which of the following supports the senior data engineer's claim?

  • A. Databricks Notebooks support the use of multiple languages in the same notebook
  • B. Databricks Notebooks support automatic change-tracking and versioning
  • C. Databricks Notebooks support commenting and notification comments
  • D. Databricks Notebooks support the creation of interactive data visualizations
  • E. Databricks Notebooks support real-time co-authoring on a single notebook

Answer: E


NEW QUESTION # 43
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?

  • A. By default, both the DBFS root and mounted data sources are only accessible to workspace administrators.
  • B. 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.
  • C. Neither the DBFS root nor mounted storage can be accessed when using %sh in a Databricks notebook.
  • D. 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.
  • E. The DBFS root is the most secure location to store data, because mounted storage volumes must have full public read and write permissions.

Answer: D

Explanation:
Explanation
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 systems1. DBFS is not a physical file system, but a layer over the object storage that provides a unified view of data across different data sources1. By default, the DBFS root is accessible to all users in the workspace, and the access to mounted data sources depends on the permissions of the storage account or container2. Mounted storage volumes do not need to have full public read and write permissions, but they do require a valid connection string or access key to be provided when mounting3. Both the DBFS root and mounted storage can be accessed when using %sh in a Databricks notebook, as long as the cluster has FUSE enabled4. The DBFS root does not store files in ephemeral block volumes attached to the driver, but in the object storage associated with the workspace1. Mounted directories will persist saved data to external storage between sessions, unless they are unmounted or deleted3. References: DBFS, Work with files on Azure Databricks, Mounting cloud object storage on Azure Databricks, Access DBFS with FUSE


NEW QUESTION # 44
The data governance team is reviewing user for deleting records for compliance with GDPR. The following logic has been implemented to propagate deleted requests from the user_lookup table to the user aggregate table.

Assuming that user_id is a unique identifying key and that all users have requested deletion have been removed from the user_lookup table, which statement describes whether successfully executing the above logic guarantees that the records to be deleted from the user_aggregates table are no longer accessible and why?

  • A. Yes: Delta Lake ACID guarantees provide assurance that the DELETE command successed fully and permanently purged these records.
  • B. No: the Delta Lake DELETE command only provides ACID guarantees when combined with the MERGE INTO command
  • C. No: the change data feed only tracks inserts and updates not deleted records.
  • D. No: files containing deleted records may still be accessible with time travel until a BACUM command is used to remove invalidated data files.

Answer: D

Explanation:
The DELETE operation in Delta Lake is ACID compliant, which means that once the operation is successful, the records are logically removed from the table. However, the underlying files that contained these records may still exist and be accessible via time travel to older versions of the table. To ensure that these records are physically removed and compliance with GDPR is maintained, a VACUUM command should be used to clean up these data files after a certain retention period. The VACUUM command will remove the files from the storage layer, and after this, the records will no longer be accessible.


NEW QUESTION # 45
......

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