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

Section	Weight	Objectives
Topic 1: Monitoring and Troubleshooting	16%	- Monitoring - Troubleshooting - Performance Optimization
Topic 2: Databricks Lakehouse Platform	24%	- Delta Lake - Data Management - Unity Catalog - Lakehouse Architecture
Topic 3: Data Processing	28%	- ETL Pipelines - Spark SQL - Data Transformation - Structured Streaming
Topic 4: Data Modeling and Storage	20%	- File Formats - Storage Optimization - Data Modeling
Topic 5: Data Quality and Governance	12%	- Governance - Data Lineage - Data Quality

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Databricks Certified Data Engineer Professional Exam Sample Questions (Q12-Q17):

NEW QUESTION # 12
In a Databricks Asset Bundle project, in the file resources/app.yml, the data engineer would like to deploy a Databricks Apps databricks_app_deployed and Volume volume_deployed and grant the Service Principal behind Databricks Apps permissions to READ and WRITE to the Volume.
How should the data engineer achieve the deployment?

Answer: B

Explanation:
This configuration correctly references the service principal created for the Databricks App using the deployed app resource identifier, and it grants the required READ and WRITE privileges at the Volume level. The privileges are specified using the correct Volume-specific permissions, ensuring the Databricks App can securely access the Volume after deployment.

NEW QUESTION # 13
The data governance team is reviewing code used for deleting records for compliance with GDPR. They note the following logic is used to delete records from the Delta Lake table named users.

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

A. Yes; Delta Lake ACID guarantees provide assurance that the delete command succeeded 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. Yes; the Delta cache immediately updates to reflect the latest data files recorded to disk.
D. No; the Delta cache may return records from previous versions of the table until the cluster is restarted.
E. No; files containing deleted records may still be accessible with time travel until a vacuum command is used to remove invalidated data files.

Answer: E

Explanation:
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from Explanation:
The code uses the DELETE FROM command to delete records from the users table that match a condition based on a join with another table called delete_requests, which contains all users that have requested deletion. The DELETE FROM command deletes records from a Delta Lake table by creating a new version of the table that does not contain the deleted records. However, this does not guarantee that the records to be deleted are no longer accessible, because Delta Lake supports time travel, which allows querying previous versions of the table using a timestamp or version number. Therefore, files containing deleted records may still be accessible with time travel until a vacuum command is used to remove invalidated data files from physical storage.

NEW QUESTION # 14
The data architect has mandated that all tables in the Lakehouse should be configured as external (also known as "unmanaged") Delta Lake tables.
Which approach will ensure that this requirement is met?

A. When data is saved to a table, make sure that a full file path is specified alongside the Delta format.
B. When configuring an external data warehouse for all table storage, leverage Databricks for all ELT.
C. When the workspace is being configured, make sure that external cloud object storage has been mounted.
D. When a database is being created, make sure that the LOCATION keyword is used.
E. When tables are created, make sure that the EXTERNAL keyword is used in the CREATE TABLE statement.

Answer: E

Explanation:
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from To create an external or unmanaged Delta Lake table, you need to use the EXTERNAL keyword in the CREATE TABLE statement. This indicates that the table is not managed by the catalog and the data files are not deleted when the table is dropped. You also need to provide a LOCATION clause to specify the path where the data files are stored.
For example:
CREATE EXTERNAL TABLE events ( date DATE, eventId STRING, eventType STRING, data STRING) USING DELTA LOCATION `/mnt/delta/events'; This creates an external Delta Lake table named events that references the data files in the
`/mnt/delta/events' path. If you drop this table, the data files will remain intact and you can recreate the table with the same statement.

NEW QUESTION # 15
A task orchestrator has been configured to run two hourly tasks. First, an outside system writes Parquet data to a directory mounted at /mnt/raw_orders/. After this data is written, a Databricks job containing the following code is executed:

Assume that the fields customer_id and order_id serve as a composite key to uniquely identify each order, and that the time field indicates when the record was queued in the source system.
If the upstream system is known to occasionally enqueue duplicate entries for a single order hours apart, which statement is correct?

A. Duplicate records enqueued more than 2 hours apart may be retained and the orders table may contain duplicate records with the same customer_id and order_id.
B. All records will be held in the state store for 2 hours before being deduplicated and committed to the orders table.
C. The orders table will contain only the most recent 2 hours of records and no duplicates will be present.
D. Duplicate records arriving more than 2 hours apart will be dropped, but duplicates that arrive in the same batch may both be written to the orders table.
E. The orders table will not contain duplicates, but records arriving more than 2 hours late will be ignored and missing from the table.

Answer: A

NEW QUESTION # 16
A Data Engineer is building a fraud detection pipeline that calls out to Open AI, via a Python library, and needs to include an access token when using the API. Which Databricks CLI command should the Data Engineer use to create the secret?

A. databricks tokens put-token KEY SCOPE; dbutils.secrets.get (KEY, SCOPE)
B. databricks secrets put-secret SCOPE KEY; dbutils.secrets.get (SCOPE, KEY)
C. databricks secrets put-secret KEY SCOPE; dbutils.secrets.get (KEY, SCOPE)
D. databricks tokens put-token SCOPE KEY; dbutils.tokens.get (SCOPE, KEY)

Answer: B

Explanation:
The Databricks CLI command databricks secrets put-secret <scope> <key> is used to securely store sensitive values such as API access tokens in a secret scope. The secret can then be retrieved at runtime using dbutils.secrets.get(scope, key), ensuring credentials are not hard- coded and remain protected.

NEW QUESTION # 17
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