Databricks Certified Data Engineer Associate Practice Questions: Data Governance and Security Domain
Test your Databricks Certified Data Engineer Associate knowledge with 10 practice questions from the Data Governance and Security domain. Includes detailed explanations and answers.
Databricks Certified Data Engineer Associate Practice Questions
Master the Data Governance and Security Domain
Test your knowledge in the Data Governance and Security domain with these 10 practice questions. Each question is designed to help you prepare for the Databricks Certified Data Engineer Associate certification exam with detailed explanations to reinforce your learning.
Question 1
In Databricks, what is the role of Unity Catalog in data governance?
Show Answer & Explanation
Correct Answer: A
Explanation: Unity Catalog in Databricks is designed to provide a centralized metadata repository for all data assets, enhancing data governance by enabling fine-grained access control and auditing capabilities. Option B is incorrect because Unity Catalog is not used for orchestrating data pipelines. Option C is incorrect as Unity Catalog does not manage machine learning model versioning. Option D is incorrect as it does not provide a platform for real-time data streaming.
Question 2
Which Databricks feature would you use to audit user activities and access patterns?
Show Answer & Explanation
Correct Answer: C
Explanation: Audit Logs in Databricks are used to track and audit user activities and access patterns, providing insights into who accessed what data and when. Option A is incorrect as Databricks Runtime is for running computations. Option B is incorrect because Cluster Policies are used to enforce resource configurations. Option D is incorrect as Notebook Widgets are for interactive data exploration.
Question 3
In Databricks, which feature allows you to audit and monitor access to data to ensure compliance with data governance policies?
Show Answer & Explanation
Correct Answer: C
Explanation: Unity Catalog provides centralized governance for data and AI assets, including audit logging and monitoring access to data, which is essential for compliance with data governance policies. Option A, Cluster Policies, are used to manage cluster configurations. Option B, Delta Lake, is a storage layer that provides ACID transactions. Option D, Notebook Revision History, tracks changes to notebooks but is not related to auditing data access.
Question 4
Which of the following is a best practice for ensuring data security when sharing data across different teams in Databricks?
Show Answer & Explanation
Correct Answer: C
Explanation: Implementing data masking and encryption is a best practice for ensuring data security, as it protects sensitive information by obfuscating data and securing it at rest and in transit. Using personal access tokens for all users (A) can lead to security risks if not managed properly. Granting cluster manager permissions to all users (B) can result in unnecessary access and potential misuse of resources. Disabling all audit logging (D) removes the ability to track and monitor access and changes, which is crucial for security.
Question 5
When configuring data encryption in Databricks, which of the following is a best practice to ensure data security?
Show Answer & Explanation
Correct Answer: C
Explanation: Regularly rotating encryption keys is a best practice to enhance data security, as it limits the amount of data exposed if a key is compromised. Option A is incorrect because using a single key increases risk. Option B is incorrect because disabling encryption can expose data to unauthorized access. Option D is incorrect because storing keys with the data they encrypt can lead to security vulnerabilities.
Question 6
Which of the following is a best practice for managing sensitive data in Databricks notebooks?
Show Answer & Explanation
Correct Answer: B
Explanation: Using Databricks Secrets to store sensitive data is a best practice because it provides a secure way to manage and access sensitive information without hardcoding it into notebooks. Hardcoding sensitive information (A) or storing it in plain text files (C) exposes it to unauthorized access. Sharing sensitive information via email (D) is insecure and not recommended.
Question 7
Which Databricks feature helps ensure compliance by logging detailed information about data access and usage?
Show Answer & Explanation
Correct Answer: A
Explanation: Audit Logs (A) in Databricks provide a detailed record of user actions, helping organizations ensure compliance by tracking who accessed what data and when. Delta Lake (B) is a storage layer that brings reliability to data lakes but does not track access logs. Job Monitoring (C) provides insights into job performance, not compliance. Workspace Settings (D) are configurations for the Databricks environment, not specifically for logging access.
Question 8
In Databricks, which feature allows you to manage access control for individual tables in a Unity Catalog?
Show Answer & Explanation
Correct Answer: B
Explanation: Table ACLs (Access Control Lists) in Unity Catalog allow you to manage permissions at the table level, enabling fine-grained access control. Cluster Policies (A) are used to define rules for cluster configurations. Workspace Permissions (C) manage access to the Databricks workspace itself, not individual tables. Secrets Management (D) is used for securely storing and accessing sensitive information like API keys and passwords, not for table access control.
Question 9
Which of the following is the primary purpose of using Access Control Lists (ACLs) in Databricks?
Show Answer & Explanation
Correct Answer: B
Explanation: The primary purpose of Access Control Lists (ACLs) in Databricks is to enforce security policies by restricting access to data and resources. ACLs help ensure that only authorized users have access to specific datasets or resources. Option A is incorrect because ACLs are not used for managing costs. Option C is incorrect as ACLs do not improve query performance. Option D is incorrect because ACLs are not related to deploying machine learning models.
Question 10
Which of the following is the primary purpose of implementing role-based access control (RBAC) in a Databricks environment?
Show Answer & Explanation
Correct Answer: B
Explanation: The primary purpose of implementing RBAC is to enforce the principle of least privilege by ensuring that users have access only to the data and resources necessary for their job roles. This minimizes the risk of data breaches and unauthorized access. Option A is incorrect because RBAC is not related to resource deployment. Option C is incorrect as RBAC does not directly affect performance. Option D is incorrect because RBAC is not used for data replication.
Ready to Accelerate Your Databricks Certified Data Engineer Associate Preparation?
Join thousands of professionals who are advancing their careers through expert certification preparation with FlashGenius.
- ✅ Unlimited practice questions across all Databricks Certified Data Engineer Associate domains
- ✅ Full-length exam simulations with real-time scoring
- ✅ AI-powered performance tracking and weak area identification
- ✅ Personalized study plans with adaptive learning
- ✅ Mobile-friendly platform for studying anywhere, anytime
- ✅ Expert explanations and study resources
Already have an account? Sign in here
About Databricks Certified Data Engineer Associate Certification
The Databricks Certified Data Engineer Associate certification validates your expertise in data governance and security and other critical domains. Our comprehensive practice questions are carefully crafted to mirror the actual exam experience and help you identify knowledge gaps before test day.