Databricks Certified Data Engineer
Associate Exam Questions And Correct
Answers (Verified Answers) Plus
Rationales 2026 Q&A | Instant
Download Pdf
Question 1
What is the primary purpose of the Databricks Lakehouse architecture?
A. To replace SQL databases entirely
B. To combine data lakes and data warehouses into a unified platform
C. To eliminate the need for ETL pipelines
D. To store only structured data
Rationale: The Lakehouse architecture integrates the scalability and low-cost
storage of data lakes with the performance and management features of data
warehouses. This unified approach enables analytics and machine learning on a
single platform without duplicating data systems.
Question 2
Which file format is most commonly optimized for Delta Lake tables?
A. CSV
B. JSON
C. ORC
D. Parquet
,Rationale: Delta Lake is built on top of Parquet files, which provide efficient
columnar storage, compression, and fast query performance. Delta adds
transaction logs on top of Parquet for reliability.
Question 3
What does ACID in Delta Lake guarantee?
A. Availability, Consistency, Isolation, Durability
B. Aggregation, Compression, Indexing, Distribution
C. Atomicity, Consistency, Isolation, Durability
D. Accuracy, Concurrency, Integrity, Deduplication
Rationale: ACID properties ensure reliable transactions in Delta Lake. They
guarantee that operations are completed fully or not at all, maintain
consistency, isolate concurrent operations, and ensure durability after commits.
Question 4
Which command is used to create a Delta table in Spark SQL?
A. CREATE TABLE AS JSON
B. CREATE TABLE USING CSV
C. CREATE TABLE USING DELTA
D. MAKE TABLE DELTA
Rationale: Delta tables are created using the “USING DELTA” syntax in Spark
SQL, enabling Delta Lake features such as versioning and ACID transactions.
Question 5
What is the purpose of Delta Lake transaction logs?
A. Store backup copies of data
B. Store user permissions
,C. Track changes and enable ACID compliance
D. Compress Parquet files
Rationale: The transaction log (Delta log) records all changes made to a table,
enabling version control, rollback, and ACID compliance for distributed
processing.
Question 6
Which Databricks feature helps manage streaming and batch data in one system?
A. MLflow
B. Delta Sharing
C. Delta Lake
D. Databricks Repos
Rationale: Delta Lake enables both streaming and batch processing on the same
tables, allowing unified data pipelines without separate architectures.
Question 7
What is a key benefit of Auto Loader in Databricks?
A. Manual schema enforcement
B. Only supports batch ingestion
C. Automatically detects and processes new files incrementally
D. Requires Hive metastore configuration only
Rationale: Auto Loader simplifies incremental data ingestion by automatically
detecting new files in cloud storage and processing them efficiently at scale.
Question 8
Which language is NOT natively supported in Databricks notebooks?
, A. Python
B. SQL
C. Scala
D. C++
Rationale: Databricks supports Python, SQL, Scala, and R, but does not support
C++ in its notebook environment.
Question 9
What does OPTIMIZE do in Delta Lake?
A. Deletes old clusters
B. Compresses notebook outputs
C. Combines small files into larger ones for performance
D. Encrypts data at rest
Rationale: OPTIMIZE improves query performance by compacting small files into
larger Parquet files, reducing overhead during reads.
Question 10
What is ZORDER used for in Databricks?
A. Data encryption
B. Schema validation
C. Clustering data for faster query performance
D. Streaming ingestion
Rationale: ZORDER improves query performance by colocating related data in
the same files based on specified columns, reducing scan time.
Question 11
Which command is used to remove a Delta table?
Associate Exam Questions And Correct
Answers (Verified Answers) Plus
Rationales 2026 Q&A | Instant
Download Pdf
Question 1
What is the primary purpose of the Databricks Lakehouse architecture?
A. To replace SQL databases entirely
B. To combine data lakes and data warehouses into a unified platform
C. To eliminate the need for ETL pipelines
D. To store only structured data
Rationale: The Lakehouse architecture integrates the scalability and low-cost
storage of data lakes with the performance and management features of data
warehouses. This unified approach enables analytics and machine learning on a
single platform without duplicating data systems.
Question 2
Which file format is most commonly optimized for Delta Lake tables?
A. CSV
B. JSON
C. ORC
D. Parquet
,Rationale: Delta Lake is built on top of Parquet files, which provide efficient
columnar storage, compression, and fast query performance. Delta adds
transaction logs on top of Parquet for reliability.
Question 3
What does ACID in Delta Lake guarantee?
A. Availability, Consistency, Isolation, Durability
B. Aggregation, Compression, Indexing, Distribution
C. Atomicity, Consistency, Isolation, Durability
D. Accuracy, Concurrency, Integrity, Deduplication
Rationale: ACID properties ensure reliable transactions in Delta Lake. They
guarantee that operations are completed fully or not at all, maintain
consistency, isolate concurrent operations, and ensure durability after commits.
Question 4
Which command is used to create a Delta table in Spark SQL?
A. CREATE TABLE AS JSON
B. CREATE TABLE USING CSV
C. CREATE TABLE USING DELTA
D. MAKE TABLE DELTA
Rationale: Delta tables are created using the “USING DELTA” syntax in Spark
SQL, enabling Delta Lake features such as versioning and ACID transactions.
Question 5
What is the purpose of Delta Lake transaction logs?
A. Store backup copies of data
B. Store user permissions
,C. Track changes and enable ACID compliance
D. Compress Parquet files
Rationale: The transaction log (Delta log) records all changes made to a table,
enabling version control, rollback, and ACID compliance for distributed
processing.
Question 6
Which Databricks feature helps manage streaming and batch data in one system?
A. MLflow
B. Delta Sharing
C. Delta Lake
D. Databricks Repos
Rationale: Delta Lake enables both streaming and batch processing on the same
tables, allowing unified data pipelines without separate architectures.
Question 7
What is a key benefit of Auto Loader in Databricks?
A. Manual schema enforcement
B. Only supports batch ingestion
C. Automatically detects and processes new files incrementally
D. Requires Hive metastore configuration only
Rationale: Auto Loader simplifies incremental data ingestion by automatically
detecting new files in cloud storage and processing them efficiently at scale.
Question 8
Which language is NOT natively supported in Databricks notebooks?
, A. Python
B. SQL
C. Scala
D. C++
Rationale: Databricks supports Python, SQL, Scala, and R, but does not support
C++ in its notebook environment.
Question 9
What does OPTIMIZE do in Delta Lake?
A. Deletes old clusters
B. Compresses notebook outputs
C. Combines small files into larger ones for performance
D. Encrypts data at rest
Rationale: OPTIMIZE improves query performance by compacting small files into
larger Parquet files, reducing overhead during reads.
Question 10
What is ZORDER used for in Databricks?
A. Data encryption
B. Schema validation
C. Clustering data for faster query performance
D. Streaming ingestion
Rationale: ZORDER improves query performance by colocating related data in
the same files based on specified columns, reducing scan time.
Question 11
Which command is used to remove a Delta table?
