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

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

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Databricks Certified Professional Data Engineer Exam Sample Questions (Q224-Q229):

NEW QUESTION # 224
Which one of the following is not a Databricks lakehouse object?

Answer: F

Explanation:
Explanation
The answer is, Stored Procedures.
Databricks lakehouse does not support stored procedures.


NEW QUESTION # 225
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.table("bronze")
B . return spark.readStream.load("bronze")
C .

D .
return spark.read.option("readChangeFeed", "true").table ("bronze")
E .

Answer: C

Explanation:
https://docs.databricks.com/en/delta/delta-change-data-feed.html


NEW QUESTION # 226
A developer has successfully configured credential for Databricks Repos and cloned a remote Git repository.
Hey don not have privileges to make changes to the main branch, which is the only branch currently visible in their workspace.
Use Response to pull changes from the remote Git repository commit and push changes to a branch that appeared as a changes were pulled.

Answer: C

Explanation:
In Databricks Repos, when a user does not have privileges to make changes directly to the main branch of a cloned remote Git repository, the recommended approach is to create a new branch within the Databricks workspace. The developer can then make changes in this new branch, commit those changes, and push the new branch to the remote Git repository. This workflow allows for isolated development without affecting the main branch, enabling the developer to propose changes via a pull request from the new branch to the main branch in the remote repository. This method adheres to common Git collaboration workflows, fostering code review and collaboration while ensuring the integrity of the main branch.
References:
* Databricks documentation on using Repos with Git: https://docs.databricks.com/repos.html


NEW QUESTION # 227
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?

Answer: B

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 # 228
The data architect has decided that once data has been ingested from external sources into the Databricks Lakehouse, table access controls will be leveraged to manage permissions for all production tables and views.
The following logic was executed to grant privileges for interactive queries on a production database to the core engineering group.
GRANT USAGE ON DATABASE prod TO eng;
GRANT SELECT ON DATABASE prod TO eng;
Assuming these are the only privileges that have been granted to the eng group and that these users are not workspace administrators, which statement describes their privileges?

Answer: D

Explanation:
The GRANT USAGE ON DATABASE prod TO eng command grants the eng group the permission to use the prod database, which means they can list and access the tables and views in the database. The GRANT SELECT ON DATABASE prod TO eng command grants the eng group the permission to select data from the tables and views in the prod database, which means they can query the data using SQL or DataFrame API.
However, these commands do not grant the eng group any other permissions, such as creating, modifying, or deleting tables and views, or defining custom functions. Therefore, the eng group members are able to query all tables and views in the prod database, but cannot create or edit anything in the database. References:
* Grant privileges on a database: https://docs.databricks.com/en/security/auth-authz/table-acls/grant- privileges-database.html
* Privileges you can grant on Hive metastore objects: https://docs.databricks.com/en/security/auth-authz
/table-acls/privileges.html


NEW QUESTION # 229
......

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