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

Databricks Certified Data Engineer Professional Sample Questions:

1. The data engineering team has configured a job to process customer requests to be forgotten (have their data deleted). All user data that needs to be deleted is stored in Delta Lake tables using default table settings.
The team has decided to process all deletions from the previous week as a batch job at 1am each Sunday. The total duration of this job is less than one hour. Every Monday at 3am, a batch job executes a series of VACUUM commands on all Delta Lake tables throughout the organization.
The compliance officer has recently learned about Delta Lake's time travel functionality. They are concerned that this might allow continued access to deleted data.
Assuming all delete logic is correctly implemented, which statement correctly addresses this concern?

A) Because the default data retention threshold is 24 hours, data files containing deleted records will be retained until the vacuum job is run the following day.
B) Because Delta Lake's delete statements have ACID guarantees, deleted records will be permanently purged from all storage systems as soon as a delete job completes.
C) Because Delta Lake time travel provides full access to the entire history of a table, deleted records can always be recreated by users with full admin privileges.
D) Because the default data retention threshold is 7 days, data files containing deleted records will be retained until the vacuum job is run 8 days later.
E) Because the vacuum command permanently deletes all files containing deleted records, deleted records may be accessible with time travel for around 24 hours.

2. A team of data engineer are adding tables to a DLT pipeline that contain repetitive expectations for many of the same data quality checks.
One member of the team suggests reusing these data quality rules across all tables defined for this pipeline.
What approach would allow them to do this?

A) Maintain data quality rules in a separate Databricks notebook that each DLT notebook of file.
B) Maintain data quality rules in a Delta table outside of this pipeline's target schema, providing the schema name as a pipeline parameter.
C) Add data quality constraints to tables in this pipeline using an external job with access to pipeline configuration files.
D) Use global Python variables to make expectations visible across DLT notebooks included in the same pipeline.

3. A data engineer created a daily batch ingestion pipeline using a cluster with the latest DBR version to store banking transaction data, and persisted it in a MANAGED DELTA table called prod.gold.all_banking_transactions_daily. The data engineer is constantly receiving complaints from business users who query this table ad hoc through a SQL Serverless Warehouse about poor query performance. Upon analysis, the data engineer identified that these users frequently use high- cardinality columns as filters. The engineer now seeks to implement a data layout optimization technique that is incremental, easy to maintain, and can evolve over time. Which command should the data engineer implement?

A) Alter the table to use Z-ORDER and implement a periodic OPTIMIZE command.
B) Alter the table to use Hive-Style Partitions + Z-ORDER and implement a periodic OPTIMIZE command.
C) Alter the table to use Hive-Style Partitions and implement a periodic OPTIMIZE command.
D) Alter the table to use Liquid Clustering and implement a periodic OPTIMIZE command.

4. A data engineer has created a new cluster using shared access mode with default configurations.
The data engineer needs to allow the development team access to view the driver logs if needed.
What are the minimal cluster permissions that allow the development team to accomplish this?

A) CAN ATTACH TO
B) CAN RESTART
C) CAN VIEW
D) CAN MANAGE

5. Assuming that the Databricks CLI has been installed and configured correctly, which Databricks CLI command can be used to upload a custom Python Wheel to object storage mounted with the DBFS for use with a production job?

A) configure
B) libraries
C) fs
D) jobs
E) workspace

Solutions: