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Databricks Databricks-Certified-Professional-Data-Engineer Exam Syllabus Topics:

Section	Objectives
Topic 1: Data Modeling and Storage	- Design scalable data lakehouse architectures - Schema evolution and data partitioning strategies - Delta Lake table design and optimization
Topic 2: Data Ingestion and Transformation	- Ingest data using Apache Spark and Databricks - Handle batch and streaming data pipelines - Transform and clean datasets using Spark SQL and DataFrame APIs
Topic 3: Security, Governance, Monitoring, and Optimization	- Cost optimization and performance tuning - Implement Unity Catalog governance and access control - Monitor and optimize Spark workloads
Topic 4: Production Pipelines and Orchestration	- Automate ETL pipelines and scheduling - Pipeline reliability and fault tolerance - Build and manage workflows using Databricks Jobs

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Databricks Certified Professional Data Engineer Exam Sample Questions (Q214-Q219):

NEW QUESTION # 214
A data engineer is designing a data pipeline in Databricks that needs to process records from a Kafka stream where late-arriving data is common. Which approach should the data engineer use?

A. Use a watermark to specify the allowed lateness to accommodate records that arrive after their expected window, ensuring correct aggregation and state management.
B. Use batch processing and overwrite the entire output table each time to ensure late data is incorporated correctly.
C. Use an Auto CDC pipeline with batch tables to simplify late data handling.
D. Implement a custom solution using Databricks Jobs to periodically reprocess all historical data.

Answer: A

Explanation:
Databricks and Apache Spark document watermarks as the standard mechanism for handling late-arriving data in Structured Streaming. A watermark defines how long the engine should continue waiting for out-of- order event-time data and helps manage state for aggregations, joins, and deduplication. ( Databricks Documentation ) This directly matches Kafka streaming scenarios where lateness is common. The other options are not the standard streaming solution for event-time late data: Auto CDC is for change data capture use cases, and repeated full historical reprocessing is inefficient and unnecessary when watermarking is the built-in feature designed for this problem. ( Databricks Documentation )
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NEW QUESTION # 215
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 succeed; the string " redacted " will be printed.
D. The connection to the external table will fail; the string " redacted " will be printed.
E. The connection to the external table will succeed; the string value of password will be printed in plain text.

Answer: C

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 and Governance" section; Databricks Documentation, under
"Secrets" section.

NEW QUESTION # 216
The data engineering team noticed that one of the job normally finishes in 15 mins but gets stuck randomly when reading remote databases due to a network packet drop, which of the following steps can be used to improve the stability of the job?

A. Use Jobs runs, active runs UI section to monitor and kill long running job
B. Use Databrick REST API to monitor long running jobs and issue a kill command
C. Use Spark job time out setting in the Spark UI
D. Use Cluster timeout setting in the Job cluster UI
E. Modify the task, to include a timeout to kill the job if it runs more than 15 mins.

Answer: E

Explanation:
Explanation
The answer is, Modify the task, to include time out to kill the job if it runs more than 15 mins.
https://docs.microsoft.com/en-us/azure/databricks/data-engineering/jobs/jobs#timeout

NEW QUESTION # 217
You have configured AUTO LOADER to process incoming IOT data from cloud object storage every 15 mins, recently a change was made to the notebook code to update the processing logic but the team later realized that the notebook was failing for the last 24 hours, what steps team needs to take to reprocess the data that was not loaded after the notebook was corrected?

A. Manually re-load the data
B. Enable back_fill = TRUE to reprocess the data
C. Move the files that were not processed to another location and manually copy the files into the ingestion path to reprocess them
D. Autoloader automatically re-processes data that was not loaded
E. Delete the checkpoint folder and run the autoloader again

Answer: D

Explanation:
Explanation
The answer is,
Autoloader automatically re-processes data that was not loaded using the checkpoint.

NEW QUESTION # 218
You are trying to create an object by joining two tables that and it is accessible to data scientist's team, so it does not get dropped if the cluster restarts or if the notebook is detached. What type of object are you trying to create?

A. External view
B. View
C. Temporary view
D. Global Temporary view with cache option
E. Global Temporary view

Answer: B

Explanation:
Explanation
Answer is View, A view can be used to join multiple tables but also persist into meta stores so others can accesses it

NEW QUESTION # 219
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