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

Databricks Certified Data Engineer Professional Sample Questions:

1. A DLT pipeline includes the following streaming tables:
Raw_lot ingest raw device measurement data from a heart rate tracking device.
Bpm_stats incrementally computes user statistics based on BPM measurements from raw_lot.
How can the data engineer configure this pipeline to be able to retain manually deleted or updated records in the raw_iot table while recomputing the downstream table when a pipeline update is run?

A) Set the pipelines, reset, allowed property to false on raw_iot
B) Set the skipChangeCommits flag to true on bpm_stats
C) Set the SkipChangeCommits flag to true raw_lot
D) Set the pipelines, reset, allowed property to false on bpm_stats

2. In order to facilitate near real-time workloads, a data engineer is creating a helper function to leverage the schema detection and evolution functionality of Databricks Auto Loader. The desired function will automatically detect the schema of the source directly, incrementally process JSON files as they arrive in a source directory, and automatically evolve the schema of the table when new fields are detected.
The function is displayed below with a blank:

Which response correctly fills in the blank to meet the specified requirements?

A)

B)

C)

D)

E)

3. The data governance team has instituted a requirement that the "user" table containing Personal Identifiable Information (PII) must have the appropriate masking on the SSN column. This means that anyone outside of the HRAdminGroup should see masked social security numbers as ***-**-
****.
The team created a masking function:

What does the data governance team need to do next to achieve this goal?

A) CREATE TABLE users
(name STRING);
ALTER TABLE users CREATE COLUMN ssn CREATE MASK ssn_mask;
B) CREATE TABLE users
(name STRING, int STRING);
ALTER TABLE users ALTER COLUMN ssn CREATE MASK if is_member('HRAdminGroup');
C) CREATE TABLE users
(name STRING, ssn STRING);
ALTER TABLE users ALTER COLUMN ssn SET MASK ssn_mask;
D) CREATE TABLE users
(name STRING, ssn INT MASKED ssn_mask);

4. An external object storage container has been mounted to the location /mnt/finance_eda_bucket.
The following logic was executed to create a database for the finance team:

After the database was successfully created and permissions configured, a member of the finance team runs the following code:

If all users on the finance team are members of the finance group, which statement describes how the tx_sales table will be created?

A) A logical table will persist the query plan to the Hive Metastore in the Databricks control plane.
B) A managed table will be created in the DBFS root storage container.
C) An external table will be created in the storage container mounted to /mnt/finance eda bucket.
D) An managed table will be created in the storage container mounted to /mnt/finance_eda_bucket.
E) A logical table will persist the physical plan to the Hive Metastore in the Databricks control plane.

5. What describes a primary technical challenge in ensuring consistent PII masking across all nodes in large-scale, distributed Databricks batch and streaming pipelines?

A) Dynamic data masking is applied only at rest, so it does not affect query performance.
B) Masking functions must be standardized and managed through Unity Catalog, with enforcement applied across all relevant datasets to avoid any data inconsistency.
C) Native masking in Databricks automatically synchronizes with all downstream external Databricks systems.
D) PII masking is only required for direct identifiers.

Solutions: