Free Databricks-Certified-Data-Engineer-Associate: Databricks Certified Data Engineer Associate Exam Questions and Answers
83 verified practice questions for Databricks-Certified-Data-Engineer-Associate.
The first 10 questions on this page are free to read, answers included — no account and no card. A plan opens the rest of the bank, the full timed practice test and your weak-topic reporting.
Last updated: September 19, 2026
- Provider
- Databricks
- Questions in our bank
- 1000+
- Free to read
- First 10, with answers
- Our test mode duration & pass mark
- 130 mins · 70%
- Verified answers
- Reviewed weekly
- Practice format
- Multiple choice
Recommended: Switch to Test Mode to start a practice test that simulates the real exam experience.
Question #1
Which of the following commands will return the location of database customer360?
Please select an optionIncorrectCorrect answer: C
To retrieve the location of a database named "customer360" in a database management system like Hive or Databricks, you can use the DESCRIBE DATABASE command followed by the database name. This command will provide information about the database, including its location.
Was this answer correct?Question #2
Which of the following describes when to use the CREATE STREAMING LIVE TABLE (formerly CREATE INCREMENTAL LIVE TABLE) syntax over the CREATE LIVE TABLE syntax when creating Delta Live Tables (DLT) tables using SQL?
Please select an optionIncorrectCorrect answer: B
The CREATE STREAMING LIVE TABLE syntax is used when you want to create Delta Live Tables (DLT) tables that are designed for processing data incrementally. This is typically used when your data pipeline involves streaming or incremental data updates, and you want the table to stay up to date as new data arrives. It allows you to define tables that can handle data changes incrementally without the need for full table refreshes.
Was this answer correct?Question #3
A data engineer is attempting to drop a Spark SQL table my_table and runs the following command: DROP TABLE IF EXISTS my_table; After running this command, the engineer notices that the data files and metadata files have been deleted from the file system. Which of the following describes why all of these files were deleted?
Please select an optionIncorrectCorrect answer: A
managed tables files and metadata are managed by metastore and will be deleted when the table is dropped . while external tables the metadata is stored in a external location. hence when a external table is dropped you clear off only the metadata and the files (data) remain.
Was this answer correct?Question #4
Which of the following data lakehouse features results in improved data quality over a traditional data lake?
Please select an optionIncorrectCorrect answer: B
One of the key features of a data lakehouse that results in improved data quality over a traditional data lake is its support for ACID (Atomicity, Consistency, Isolation, Durability) transactions. ACID transactions provide data integrity and consistency guarantees, ensuring that operations on the data are reliable and that data is not left in an inconsistent state due to failures or concurrent access. In a traditional data lake, such transactional guarantees are often lacking, making it challenging to maintain data quality, especially in scenarios involving multiple data writes, updates, or complex transformations. A data lakehouse, by offering ACID compliance, helps maintain data quality by providing strong consistency and reliability, which is crucial for data pipelines and analytics.
Was this answer correct?Question #5
Which of the following statements regarding the relationship between Silver tables and Bronze tables is always true?
Please select an optionIncorrectCorrect answer: D
https://www.databricks.com/glossary/medallion-architecture
Was this answer correct?Question #6
Which of the following describes the relationship between Bronze tables and raw data?
Please select an optionIncorrectCorrect answer: E
The Bronze layer is where we land all the data from external source systems. The table structures in this layer correspond to the source system table structures "as-is," along with any additional metadata columns that capture the load date/time, process ID, etc. The focus in this layer is quick Change Data Capture and the ability to provide an historical archive of source (cold storage), data lineage, auditability, reprocessing if needed without rereading the data from the source system.https://www.databricks.com/glossary/medallion- architecture#:~:text=Bronze%20layer%20%28raw%20data%29
Was this answer correct?Question #7
A data engineer wants to create a new table containing the names of customers that live in France. They have written the following command: A senior data engineer mentions that it is organization policy to include a table property indicating that the new table includes personally identifiable information (PII). Which of the following lines of code fills in the above blank to successfully complete the task?
Please select an optionIncorrectCorrect answer: D
Ref:https://www.databricks.com/discover/pages/data-quality-management CREATE TABLE my_table (id INT COMMENT 'Unique Identification Number', name STRING COMMENT 'PII', age INT COMMENT 'PII') TBLPROPERTIES ('contains_pii'=True) COMMENT 'Contains PII';
Was this answer correct?Question #8
Which of the following benefits of using the Databricks Lakehouse Platform is provided by Delta Lake?
Please select an optionIncorrectCorrect answer: D
Delta Lake is a key component of the Databricks Lakehouse Platform that provides several benefits, and one of the most significant benefits is its ability to support both batch and streaming workloads seamlessly. Delta Lake allows you to process and analyze data in real-time (streaming) as well as in batch, making it a versatile choice for various data processing needs. While the other options may be benefits or capabilities of Databricks or the Lakehouse Platform in general, they are not specifically associated with Delta Lake.
Was this answer correct?Question #9
Which of the following commands can be used to write data into a Delta table while avoiding the writing of duplicate records?
Please select an optionIncorrectCorrect answer: C
To write data into a Delta table while avoiding the writing of duplicate records, you can use the MERGE command. The MERGE command in Delta Lake allows you to combine the ability to insert new records and update existing records in a single atomic operation. The MERGE command compares the data being written with the existing data in the Delta table based on specified matching criteria, typically using a primary key or unique identifier. It then performs conditional actions, such as inserting new records or updating existing records, depending on the comparison results. By using the MERGE command, you can handle the prevention of duplicate records in a more controlled and efficient manner. It allows you to synchronize and reconcile data from different sources while avoiding duplication and ensuring data integrity.
Was this answer correct?Question #10
A data engineer has a Python notebook in Databricks, but they need to use SQL to accomplish a specific task within a cell. They still want all of the other cells to use Python without making any changes to those cells. Which of the following describes how the data engineer can use SQL within a cell of their Python notebook?
Please select an optionIncorrectCorrect answer: D
Adding %sql as the first line of a cell sets that cell's language to SQL while the notebook default stays Python, so the other cells need no change. Changing the notebook default would affect every cell.
Was this answer correct?
Continue with Databricks-Certified-Data-Engineer-Associate: Databricks Certified Data Engineer Associate Exam
Unlock the full question bank
You have read the first 10 questions. A subscription opens every question in Databricks-Certified-Data-Engineer-Associate: Databricks Certified Data Engineer Associate Exam, the full timed practice test, and your progress and weak-topic reporting.
Single exam
$19.99for 30 days
Full question bank and practice test for one exam, for 30 days.
Single exam
$49.99for 1 year
One exam for a full year. Nothing renews and nothing to cancel.
Full access
$39.99/mo
Every exam in the catalogue, month to month.
Full access
$199.99/yr
Every exam in the catalogue for a year.
Already subscribed? Sign in to pick up where you left off.
Other Databricks certifications
- Certified Machine Learning Associate (opens in a new tab)
- Certified Machine Learning Professional (opens in a new tab)
- Certified Data Engineer Associate (opens in a new tab)
- Certified Data Analyst Associate (opens in a new tab)
- Certified Associate Developer for Apache Spark (opens in a new tab)
- Certified Data Engineer Professional (opens in a new tab)
Reviews
★★★★★
This platform is a lifesaver. The practice questions and explanations are so detailed. It’s the best study tool I’ve ever used.
Hannah Smith
USA
★★★★★
I highly recommend Exam Practice. The feedback after each test helped me improve significantly, and I passed my exams easily.
Oscar Nyström
Sweden
★★★★★
Exam Practice is worth every penny. The mock exams are realistic, and the feedback helped me focus on key areas.
Amit Sharma
India
FAQ
Learn More: https://www.databricks.com/learn/training/certification
- Q1: What are Databricks Certification Exams?
- A: Databricks Certification Exams validate your expertise in using Databricks’ unified data analytics platform. These certifications demonstrate your proficiency in data engineering, data analysis, and machine learning, utilizing Databricks tools and the Apache Spark framework.
- Q2: Why should I pursue Databricks Certification?
- A: Databricks Certification enhances your professional credibility, showcasing your skills and knowledge in big data analytics and machine learning. This can lead to better job opportunities, higher salaries, and career advancement in data science, data engineering, and IT industries.
- Q3: What are the benefits of Databricks Certification?
- A: Benefits include recognition as a certified data professional, improved job performance, access to exclusive resources, continuing education opportunities, and staying current with the latest data analytics technologies and best practices.
- Q4: Who should take Databricks Certification Exams?
- A: Data engineers, data scientists, data analysts, machine learning practitioners, and anyone involved in processing and analyzing large datasets should consider these certifications to validate their expertise and advance their careers.
- Q5: What types of Databricks Certification Exams are available?
- A: Databricks offers various certification paths, including:
- Q6: How do I prepare for Databricks Certification Exams?
- A: Preparation can include official Databricks training courses, study guides, practice exams, online tutorials, and hands-on experience with Databricks tools and the Apache Spark framework.
- Q7: Where can I take Databricks Certification Exams?
- A: Databricks Certification Exams can be taken online, providing flexibility to fit your schedule and location.
- Q8: How do Databricks Certifications impact my career?
- A: Databricks Certifications significantly boost your career by demonstrating your expertise to employers, making you a more competitive candidate for advanced roles and promotions in data science, data engineering, and IT.
- Q9: Are there any prerequisites for Databricks Certification Exams?
- A: Some exams may have prerequisites, such as foundational knowledge or prior experience with Databricks and Apache Spark. Check the specific requirements for each certification path on the Databricks website.
- Q10: How often do I need to recertify for Databricks Certifications?
- A: Databricks Certifications typically require recertification every two years to ensure that certified professionals stay updated with the latest data analytics technologies and industry practices.



