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

Databricks Certified Data Engineer Professional Sample Questions:

Question 1

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

Question 2

A data engineering team is configuring access controls in Databricks Unity Catalog. They grant the SELECT privilege on the sales catalog to the analyst_group, expecting that members of this group will automatically have SELECT access to all current and future schemas, tables, and views within the catalog. What describes the privilege inheritance behavior in Unity Catalog?

A. Granting SELECT at the catalog level applies to existing schemas and tables but not to those created in the future.
B. Privileges in Unity Catalog do not cascade; SELECT must be explicitly granted on each schema and table, even if granted at the catalog level.
C. Privileges granted at the schema level override any catalog-level privileges and prevent access unless explicitly revoked.
D. Granting SELECT on a catalog automatically applies SELECT to all current and future schemas, tables, and views within that catalog.

Question 3

The data science team has created and logged a production model using MLflow. The model accepts a list of column names and returns a new column of type DOUBLE.
The following code correctly imports the production model, loads the customers table containing the customer_id key column into a DataFrame, and defines the feature columns needed for the model.

Which code block will output a DataFrame with the schema "customer_id LONG, predictions DOUBLE"?

A. df.map(lambda x:model(x[columns])).select("customer_id, predictions")
B. df.apply(model, columns).select("customer_id, predictions")
C. model.predict(df, columns)
D. df.select("customer_id", model(*columns).alias("predictions"))
E. df.select("customer_id", pandas_udf(model, columns).alias("predictions"))

Question 4

A junior data engineer is working to implement logic for a Lakehouse table named silver_device_recordings. The source data contains 100 unique fields in a highly nested JSON structure.
The silver_device_recordings table will be used downstream for highly selective joins on a number of fields, and will also be leveraged by the machine learning team to filter on a handful of relevant fields, in total, 15 fields have been identified that will often be used for filter and join logic.
The data engineer is trying to determine the best approach for dealing with these nested fields before declaring the table schema.
Which of the following accurately presents information about Delta Lake and Databricks that may Impact their decision-making process?

A. Because Delta Lake uses Parquet for data storage, Dremel encoding information for nesting can be directly referenced by the Delta transaction log.
B. Tungsten encoding used by Databricks is optimized for storing string data: newly-added native support for querying JSON strings means that string types are always most efficient.
C. By default Delta Lake collects statistics on the first 32 columns in a table; these statistics are leveraged for data skipping when executing selective queries.
D. Schema inference and evolution on Databricks ensure that inferred types will always accurately match the data types used by downstream systems.

Question 5

A CHECK constraint has been successfully added to the Delta table named activity_details using the following logic:

A batch job is attempting to insert new records to the table, including a record where latitude =
45.50 and longitude = 212.67.
Which statement describes the outcome of this batch insert?

A. The write will include all records in the target table; any violations will be indicated in the boolean column named valid_coordinates.
B. The write will insert all records except those that violate the table constraints; the violating records will be recorded to a quarantine table.
C. The write will fail when the violating record is reached; any records previously processed will be recorded to the target table.
D. The write will fail completely because of the constraint violation and no records will be inserted into the target table.
E. The write will insert all records except those that violate the table constraints; the violating records will be reported in a warning log.

Solutions: