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Databricks Certified Data Engineer Professional - Databricks-Certified-Data-Engineer-Professional Exam Questions

QUESTION NO: 1
A junior member of the data engineering team is exploring the language interoperability of Databricks notebooks. The intended outcome of the below code is to register a view of all sales that occurred in countries on the continent of Africa that appear in the geo_lookup table.
Before executing the code, running SHOW TABLES on the current database indicates the database contains only two tables: geo_lookup and sales.

Which statement correctly describes the outcome of executing these command cells in order in an interactive notebook?

A. Both commands will succeed. Executing show tables will show that countries at and sales at have been registered as views. B. Cmd 1 will succeed and Cmd 2 will fail, countries at will be a Python variable containing a list of strings. C. Cmd 1 will succeed. Cmd 2 will search all accessible databases for a table or view named countries af: if this entity exists, Cmd 2 will succeed. D. Cmd 1 will succeed and Cmd 2 will fail, countries at will be a Python variable representing a PySpark DataFrame. E. Both commands will fail. No new variables, tables, or views will be created.

Correct Answer: B

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QUESTION NO: 2
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 Hive-Style Partitions + Z-ORDER and implement a periodic OPTIMIZE command. B. Alter the table to use Liquid Clustering and implement a periodic OPTIMIZE command. C. Alter the table to use Z-ORDER and implement a periodic OPTIMIZE command. D. Alter the table to use Hive-Style Partitions and implement a periodic OPTIMIZE command.

Correct Answer: B

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QUESTION NO: 3
A data engineer is evaluating tools to build a production-grade data pipeline. The team must process change data from cloud object storage, filter out or isolate invalid records, and ensure the timely delivery of clean data to downstream consumers. The team is small, under tight deadlines, and wants to minimize operational overhead while keeping pipelines auditable and maintainable.
Which approach should the data engineer implement?

A. Use a hybrid approach: Ingest with Auto Loader into Bronze tables, then process using SQL queries in Databricks Workflows to generate cleaned Silver and Gold tables on a schedule. B. Implement ingestion using Auto Loader with Structured Streaming, and manage invalid data handling and table updates using checkpointing and merge logic. C. Use LDP to build declarative pipelines with Streaming Tables and Materialized Views, leveraging built-in support for data expectations and incremental processing. D. Ingest data directly into Delta tables via Spark jobs, apply data quality filters using UDFs, and use LDP for creating Materialized Views.

Correct Answer: C

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QUESTION NO: 4
A member of the data engineering team has submitted a short notebook that they wish to schedule as part of a larger data pipeline. Assume that the commands provided below produce the logically correct results when run as presented.

Which command should be removed from the notebook before scheduling it as a job?

A. Cmd 2 B. Cmd 6 C. Cmd 4 D. Cmd 5 E. Cmd 3

Correct Answer: B

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QUESTION NO: 5
A data engineer needs to design an efficient pipeline that automatically processes new CSV files as they arrive in S3 storage. Which Databricks feature should the data engineer use to meet these requirements?

A. Streaming from cloud storage using standard Spark readStream with format ("csv") and format ("json") B. Traditional batch processing with scheduled Databricks Jobs C. Auto Loader with schema inference and evolution enabled D. COPY INTO SQL command with parameters to track processed files

Correct Answer: C

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QUESTION NO: 6
When monitoring a complex workload, being able to see the query plan is critical to understanding what the workload is doing. Where can the visualization of the query plan be found?

A. In the Spart UI, under the Jobs tab B. In the Query Profiler, under the Stages tab C. In the Query Profiler, under Query Source D. In the Spark UI, under the SQL/DataFrame tab

Correct Answer: D

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QUESTION NO: 7
A Databricks job has been configured with 3 tasks, each of which is a Databricks notebook. Task A does not depend on other tasks. Tasks B and C run in parallel, with each having a serial dependency on task A.
If tasks A and B complete successfully but task C fails during a scheduled run, which statement describes the resulting state?

A. All logic expressed in the notebook associated with task A will have been successfully completed; tasks B and C will not commit any changes because of stage failure. B. Unless all tasks complete successfully, no changes will be committed to the Lakehouse; because task C failed, all commits will be rolled back automatically. C. All logic expressed in the notebook associated with tasks A and B will have been successfully completed; any changes made in task C will be rolled back due to task failure. D. Because all tasks are managed as a dependency graph, no changes will be committed to the Lakehouse until ail tasks have successfully been completed. E. All logic expressed in the notebook associated with tasks A and B will have been successfully completed; some operations in task C may have completed successfully.

Correct Answer: E

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QUESTION NO: 8
Which distribution does Databricks support for installing custom Python code packages?

A. CRAM B. nom C. sbt D. jars E. Wheels F. CRAN

Correct Answer: B

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QUESTION NO: 9
A data engineer is implementing Unity Catalog governance for a multi-team environment. Data scientists need interactive clusters for basic data exploration tasks, while automated ETL jobs require dedicated processing. How should the data engineer configure cluster isolation policies to enforce least privilege and ensure Unity Catalog compliance?

A. Configure all clusters with NO ISOLATION_SHARED access mode since Unity Catalog works with any cluster configuration. B. Allow all users to create any cluster type and rely on manual configuration to enable Unity Catalog access modes. C. Create compute policies with STANDARD access mode for interactive workloads and DEDICATED access mode for automated jobs. D. Use only DEDICATED access mode for both interactive workloads and automated jobs to maximize security isolation.

Correct Answer: C

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QUESTION NO: 10
A data engineer is implementing a job to download multiple PDF files from a third-party provided REST API endpoint by specifying different report types. The REST API is time-consuming and encounters intermittent errors, so the engineer wants to track each download activity to know when it fails and to retry partially, while providing scalable throughput. The engineer needs to download ten report types, and the list can be changed over time. How should the data engineer achieve this?

A. Use a foreach task with a list of report types as its inputs. B. Define a list variable within a Notebook to loop through the report types to download them, and print the download results. Execute it as a Notebook tasks. C. Use a Delta Lake table to track each report download status as 10 rows, and use it as a source table to execute the download function as a Pandas UDF. D. Define ten Notebook tasks to clearly track which report download failed.

Correct Answer: A

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