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Databricks Certified Data Engineer Professional Sample Questions:

1. A data engineer wants to ingest a large collection of image files (JPEG and PNG) from cloud object storage into a Unity Catalog-managed table for analysis and visualization. Which two configurations and practices are recommended to incrementally ingest these images into the table? (Choose two.)

A) Use Auto Loader and set cloudFiles.format to "IMAGE".
B) Use the pathGlobFilter option to select only image files (e.g., "*.jpg,*.png").
C) Use Auto Loader and set cloudFiles.format to "TEXT".
D) Use Auto Loader and set cloudFiles.format to "BINARYFILE".
E) Move files to a volume and read with SQL editor.

2. The data engineering team maintains the following code:

Assuming that this code produces logically correct results and the data in the source tables has been de-duplicated and validated, which statement describes what will occur when this code is executed?

A) An incremental job will detect if new rows have been written to any of the source tables; if new rows are detected, all results will be recalculated and used to overwrite the enriched_itemized_orders_by_account table.
B) No computation will occur until enriched_itemized_orders_by_account is queried; upon query materialization, results will be calculated using the current valid version of data in each of the three tables referenced in the join logic.
C) An incremental job will leverage information in the state store to identify unjoined rows in the source tables and write these rows to the enriched_iteinized_orders_by_account table.
D) A batch job will update the enriched_itemized_orders_by_account table, replacing only those rows that have different values than the current version of the table, using accountID as the primary key.
E) The enriched_itemized_orders_by_account table will be overwritten using the current valid version of data in each of the three tables referenced in the join logic.

3. A data engineering team is collaborating on a Databricks project where each team member needs to develop and test code independently before merging changes into the main branch.
They want to avoid accidental overwrites or branch switching issues while ensuring that all work is version- controlled and can be integrated into their CI/CD pipeline.
How should the data engineer achieve collaboration?

A) Team members use the Databricks CLI to clone the Git repository and perform Git operations from a cluster's web terminal.
B) All team members work in the same Databricks Git folder and perform Git operations (pull, push, commit, branch switching) directly in that shared folder.
C) Each team member creates their own Databricks Git folder, mapped to the same remote Git repository, and works in their own development branch within their personal folder.
D) Team members edit notebooks directly in the workspace's shared folder and periodically copy changes into a Git folder for version control.

4. A table named user_ltv is being used to create a view that will be used by data analysts on various teams. Users in the workspace are configured into groups, which are used for setting up data access using ACLs.
The user_ltv table has the following schema:
email STRING, age INT, ltv INT
The following view definition is executed:

An analyst who is not a member of the auditing group executes the following query:
SELECT * FROM user_ltv_no_minors
Which statement describes the results returned by this query?

A) All columns will be displayed normally for those records that have an age greater than 18; records not meeting this condition will be omitted.
B) All values for the age column will be returned as null values, all other columns will be returned with the values in user_ltv.
C) All age values less than 18 will be returned as null values all other columns will be returned with the values in user_ltv.
D) All columns will be displayed normally for those records that have an age greater than 17; records not meeting this condition will be omitted.
E) All records from all columns will be displayed with the values in user_ltv.

5. A data company uses Databricks Unity Catalog and has multiple enterprise data sources, including PostgreSQL, Snowflake, and SQL Server. The central data platform team wants to configure Lakehouse Federation so analysts can query external tables directly in Databricks using Databricks SQL, without duplicating data. Which steps are necessary to configure Lakehouse Federation in a secure and governed manner?

A) Create external locations and storage credentials to connect to each database, then register foreign tables in Unity Catalog.
B) Mirror the external datasets into Delta Lake using Auto Loader, and govern them using Data Lineage and System Tables.
C) Use Partner Connect to create linked datasets, and apply table ACLs at the source system to govern access through Databricks.
D) Configure connections and foreign catalog in Unity Catalog, then grant access to foreign catalogs, schemas, and tables using Unity Catalog permissions.

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