What is the purpose of maintaining audit logs for data purging operations?

To track user access to the data

To provide evidence of compliance with retention policies

A streaming pipeline ingests IoT sensor data. The `device_id` is PII and must be masked in real-time. However, the masked value must be consistent across multiple streams (e.g., sensor data and maintenance logs) so that joins can be performed. Which approach should they use?

Use a deterministic hash function (e.g., SHA-256) on the `device_id` in both streaming pipelines.

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

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

Mask the `device_id` in one stream and leave it unmasked in the other.

A company stores customer phone numbers in a Delta table. The compliance team requires that the phone numbers be masked so that only the last two digits are visible. The masked value must be used for analytics but must not be reversible. Which masking function should they apply?

Use a format-preserving encryption (FPE) algorithm.

Use a tokenization service that replaces the phone number with a random token.

Use a redaction function to replace all but the last two digits with 'X'.

Use a hash function like SHA-256 on the full phone number.

What is the primary purpose of integrating masking and purging steps into a data pipeline design?

To improve query performance by reducing data volume

To simplify the pipeline by removing unnecessary transformations

To meet data privacy and retention requirements

To reduce storage costs by compressing data

When designing a pipeline for compliance, where should masking typically be applied?

After all transformations are complete

As early as possible in the pipeline, before data is written to intermediate storage

DatabricksCertified Data Engineer Professional

Domain 7Objective 2

Ensuring Compliance DATA-ENGINEER-PROFESSIONAL Practice Questions (Page 5)

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 21–25

21foundation · easy
What is the purpose of maintaining audit logs for data purging operations?
Select an answer first
22expert · hard
A streaming pipeline ingests IoT sensor data. The `device_id` is PII and must be masked in real-time. However, the masked value must be consistent across multiple streams (e.g., sensor data and maintenance logs) so that joins can be performed. Which approach should they use?
Select an answer first
23application · medium
A company stores customer phone numbers in a Delta table. The compliance team requires that the phone numbers be masked so that only the last two digits are visible. The masked value must be used for analytics but must not be reversible. Which masking function should they apply?
Select an answer first
24foundation · easy
What is the primary purpose of integrating masking and purging steps into a data pipeline design?
Select an answer first
25foundation · easy
When designing a pipeline for compliance, where should masking typically be applied?
Select an answer first

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