A streaming pipeline ingests chat messages. The `sender_id` is PII and must be masked in real-time. The masked value must be unique for each sender to allow for user-level analytics. Which masking function should they apply?

Use a redaction function to replace the `sender_id` with 'USER'.

Use a random tokenization service that generates a new token for each message.

Use a non-deterministic UDF that generates a random number for each record.

Use a deterministic hash function (e.g., SHA-256) on the `sender_id`.

A retail company has a batch pipeline that processes customer orders. The `email` column is PII and must be masked before the data is written to a Parquet table for analytics. The masking must be deterministic so that the same email always produces the same masked value for joins. Which approach should they use?

Use the `rand` function to generate a random number and append it to the email.

Use a UDF that generates a random UUID for each email.

Use the `sha2` function on the `email` column in the DataFrame transformation.

Use the `regexp_replace` function to replace the email domain with 'example.com'.

A batch pipeline processes employee data. The `salary` column is sensitive and must be masked so that only the range (e.g., '50k-60k') is visible to analysts. The original salary must not be recoverable. Which masking function should they apply?

Use a redaction function to replace the salary with a range string.

Use a format-preserving encryption (FPE) algorithm.

Use a tokenization service that replaces the salary with a random token.

Use a hash function on the salary value.

Which of the following is a method to verify that a purging operation was executed correctly?

Checking the row count before and after the purge

Running a SELECT * query on the purged table

A streaming pipeline ingests user activity logs. The compliance team suspects that the `user_agent` column may contain PII (e.g., device identifiers). They need to detect this in real-time and mask it if necessary. Which approach should they use?

Run a batch profiling job on the streaming data after it is written to the table.

Use a machine learning model to classify the `user_agent` column in the streaming pipeline.

Apply a regex pattern in the streaming transformation to detect and mask device identifiers in the `user_agent` column.

Mask the entire `user_agent` column without detection.

DatabricksCertified Data Engineer Professional

Domain 7Objective 2

Ensuring Compliance DATA-ENGINEER-PROFESSIONAL Practice Questions (Page 3)

Part of the Ensuring Data Security and Compliance domain, which accounts for 10% of the DATA-ENGINEER-PROFESSIONAL exam. Databricks does not publish an official question count, but from its 120-minute exam (~50–80 total, ~5–8 in this domain), expect 3–4 from this objective — we provide 28 practice questions to prepare you well beyond it. (estimate)

28questions here

6free pages

8concepts

10%of the exam

Questions 11–15

11application · medium
A streaming pipeline ingests chat messages. The `sender_id` is PII and must be masked in real-time. The masked value must be unique for each sender to allow for user-level analytics. Which masking function should they apply?
Select an answer first
12application · medium
A retail company has a batch pipeline that processes customer orders. The `email` column is PII and must be masked before the data is written to a Parquet table for analytics. The masking must be deterministic so that the same email always produces the same masked value for joins. Which approach should they use?
Select an answer first
13application · medium
A batch pipeline processes employee data. The `salary` column is sensitive and must be masked so that only the range (e.g., '50k-60k') is visible to analysts. The original salary must not be recoverable. Which masking function should they apply?
Select an answer first
14foundation · easy
Which of the following is a method to verify that a purging operation was executed correctly?
Select an answer first
15application · medium
A streaming pipeline ingests user activity logs. The compliance team suspects that the `user_agent` column may contain PII (e.g., device identifiers). They need to detect this in real-time and mask it if necessary. Which approach should they use?
Select an answer first

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