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Updated: Nov 04, 2026

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

TopicDetails
Topic 1
  • ELT with Apache Spark: It focuses on extracting data, identifying the prefix, creating a view, duplicating rows, creating a new table, utilizing the dot, parsing JSON, and defining a SQL UDF. Moreover, the topic delves into describing the security model, identifying the location of a function, and identifying the PIVOT.
Topic 2
  • Incremental Data Processing: In this topic questions about identifying Delta Lake, benefits of ACID transactions, a scenario to use an external table, location of a table, the benefits of Zordering, the kind of files, CTAS as a solution, the impact of ON VIOLATION DROP ROW and ON VIOLATION FAIL UPDATE, and the necessary component to create a new DLT pipeline. Moreover, the topic also discusses directory structure of Delta Lake files, generated column, adding a table comment, and the benefits of the MERGE command.
Topic 3
  • Databricks Lakehouse Platform: This topic covers the relationship between the data lakehouse and the data warehouse, the improvement in data quality, comparing and contrasting silver and gold tables, elements of the Databricks Platform Architecture, and differentiating between all-purpose clusters and jobs clusters. Moreover, it identifies how cluster software is versioned, how clusters can be filtered, how to use multiple languages, how to run one notebook, how notebooks can be shared, Git operations, and limitations in Databricks Notebooks. Lastly, the topic describes how clusters are terminated, how to use multiple languages, and how Databricks Repos enables CI
  • CD workflows.
Topic 4
  • Data Governance: It identifies one of the four areas of data governance, Unity Catalog securables, and the cluster security modes. It also discusses how to create a UC-enabled all-purpose cluster and a DBSQL warehouse. The topic explains how to implement data object access control, create a DBSQL warehouse, and e a UC-enabled all-purpose cluster.
Topic 5
  • Production Pipelines: It focuses on identifying the advantages of using multiple tasks in Jobs, a suitable scenario where predecessor task should be set up, CRON as an opportunity for scheduling opportunity, and how an alert can be sent via email. The topic also discusses setting up a predecessor task in Jobs, reviewing a task's execution history, and debugging a failed task. Lastly, it delves into setting up a retry policy in case of failure and creating an alert in the case of a failed task.

Reference: https://www.databricks.com/learn/certification/data-engineer-associate

Databricks Databricks-Certified-Data-Engineer-Associate Exam Overview:

Certification Vendor:Databricks
Exam Name:Databricks Certified Data Engineer Associate Exam
Exam Number:Databricks-Certified-Data-Engineer-Associate
Passing Score:70%
Exam Price:$200 USD
Available Languages:English
Related Certifications:Databricks Certified Data Analyst Associate
Certificate Validity Period:2 years
Real Exam Qty:60
Exam Duration:90 minutes
Exam Format:Multiple Choice, Multiple Select
Sample Questions:Databricks Databricks-Certified-Data-Engineer-Associate Sample Questions
Exam Way:Online proctored or in-person testing center
Pre Condition:Recommended: 6+ months of experience with Databricks and Apache Spark
Official Syllabus URL:https://www.databricks.com/learn/certification/data-engineer-associate

Databricks Certified Data Engineer Associate Sample Questions:

Question #1

A data engineer runs a statement every day to copy the previous day's sales into the table transactions. Each day's sales are in their own file in the location "/transactions/raw".
Today, the data engineer runs the following command to complete this task:

After running the command today, the data engineer notices that the number of records in table transactions has not changed.
Which of the following describes why the statement might not have copied any new records into the table?

  • A. The PARQUET file format does not support COPY INTO.
  • B. The names of the files to be copied were not included with the FILES keyword.
  • C. The COPY INTO statement requires the table to be refreshed to view the copied rows.
  • D. The format of the files to be copied were not included with the FORMAT_OPTIONS keyword.
  • E. The previous day's file has already been copied into the table.
Reveal Solution  Discussion  0

Correct Answer: E  🗳️

Question #2

A data engineer needs to enforce row-level security on main.secure.events(region STRING, event_id STRING). Members of the account group all_regions need to see all rows. All other users need to see only rows where region = 'EU'. Which SQL sequence satisfies the requirement?

  • A.
  • B.
  • C.
  • D.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #3

A data engineering team needs to ingest historical CSV files from a cloud storage location that already contains 50,000 existing files. They also expect new files to arrive continuously going forward. The team wants to use Auto Loader to incrementally process both existing files and new arrivals efficiently. Which Auto Loader mode should the team configure for this use case?

  • A. Use file notification mode only after all existing files have been processed, as it cannot efficiently handle large volumes of pre-existing files.
  • B. Use file notification mode because it scales efficiently for both large numbers of existing files and continuous new arrivals by using cloud storage events rather than repeatedly listing directories.
  • C. Use directory listing mode because it provides better performance for the initial processing of
    50,000 existing files through optimized incremental listing capabilities.
  • D. Use directory listing mode initially to process the 50,000 existing files, then reconfigure the stream to use file notification mode for ongoing ingestion of new arrivals.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #4

A data engineer is onboarding a new bronze ingestion pipeline in Databricks with Unity Catalog.
The team wants Databricks to handle storage layout, apply platform optimizations over time, and simplify lifecycle management so that when a table is dropped, its underlying data is also cleaned up according to Databricks-managed retention policies.
Which table type should the data engineer create for these ingestion tables?

  • A. Foreign tables federated from an external catalog to delegate optimization to the source system.
  • B. Temporary views over files to avoid table-level governance and lifecycle coupling.
  • C. External tables with a LOCATION pointing to an external volume for full control of file layout.
  • D. Managed tables so that Unity Catalog manages both metadata and underlying data lifecycle.
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #5

A data engineer wants to read only a subset of columns from a Delta table to reduce memory usage and improve performance. Which Spark DataFrame operation should be used?

  • A. filter
  • B. groupBy
  • C. select
  • D. orderBy
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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