Databricks Certified Data Engineer Associate Practice Questions: Production Pipelines Domain

Correct Answer: C

Explanation: Cluster policies in Databricks are used to restrict and manage cluster configurations, ensuring compliance with organizational standards and optimizing resource usage. Option A is incorrect because cluster policies are not directly related to data encryption. Option B is incorrect as the number of nodes can be specified but is not the main role of cluster policies. Option D is incorrect because cluster policies do not directly execute SQL queries; they manage configurations that can affect query execution.

Correct Answer: C

Explanation: Packaging dependencies into a wheel file and attaching it to the cluster ensures that all the necessary libraries are available in a consistent manner across different environments and jobs. Option A can lead to conflicts and is less manageable. Option B can increase startup time and complexity. Option D is not recommended as it limits the functionality to only what is provided by default, which may not be sufficient for all use cases.

Correct Answer: B

Explanation: The correct answer is B. Delta Lake provides ACID transactions, which ensure data reliability and consistency, making it ideal for production pipelines. Option A is incorrect because Delta Lake supports both batch and streaming data. Option C is incorrect because Delta Lake simplifies configuration with its built-in features. Option D is incorrect because Delta Lake is designed to handle large-scale data processing.

Correct Answer: B

Explanation: The correct answer is B. Implementing automated data validation checks within the pipeline ensures that data quality is maintained consistently and efficiently. Option A is incorrect because manual inspection is time-consuming and error-prone. Option C is incorrect because relying on a single developer for data review is not scalable or reliable. Option D is incorrect because ignoring data quality checks can lead to inaccurate results and potential business risks.

Correct Answer: B

Explanation: Databricks Jobs provide built-in support for monitoring and alerting, which is crucial for managing production pipelines and ensuring they run smoothly. Option A is incorrect because jobs can be scheduled to run at regular intervals. Option C is incorrect as jobs are designed to run automatically without manual intervention. Option D is incorrect because Databricks Jobs can be integrated with external orchestration tools for enhanced automation.

Correct Answer: B

Explanation: Option B is correct because Databricks' Auto Loader provides efficient incremental data processing and can infer schema, making it suitable for handling large volumes of incoming data. Option A is incorrect as some configuration is required, and not all file formats are automatically detected. Option C is incorrect because other methods also support streaming ingestion. Option D is incorrect because while Auto Loader minimizes data loss, it does not guarantee zero data loss.

Correct Answer: A

Explanation: Option A is correct because Delta Lake's ACID transactions and data versioning help ensure data consistency and quality in a production pipeline. Option B is incorrect because relying solely on source data quality is risky and does not ensure data integrity. Option C, while possible, is not as efficient as using built-in features like Delta Lake's capabilities. Option D is incorrect as it underutilizes Databricks' built-in functionalities for ensuring data quality.

Correct Answer: A

Explanation: Cluster policies in Databricks are used to enforce cost control and security guidelines by restricting the configurations that users can set on clusters. This helps ensure compliance with organizational policies. Option B (increasing speed) is not directly related to cluster policies, Option C (auto-scaling) is a feature of Databricks clusters but not the primary purpose of policies, and Option D (enabling Delta Lake features) is unrelated to cluster policies.

Correct Answer: B

Explanation: Using Delta Lake for managing intermediate results provides benefits like ACID transactions, schema enforcement, and efficient data storage, which optimize performance. Option A (CSV files) lacks these features and is less efficient. Option C (sequential execution) can lead to underutilization of resources. Option D (disabling caching) can lead to unnecessary recomputation and slow performance.

Correct Answer: B

Explanation: The correct answer is B. A production pipeline automates the process of data ingestion, transformation, and loading, ensuring that data is processed efficiently and consistently. Option A is incorrect because production pipelines are designed to automate tasks, not require manual triggering. Option C is incorrect because visualizing data in a dashboard is not the primary purpose of a production pipeline. Option D is incorrect because production pipelines are not meant for ad-hoc analysis but for automated and repeatable tasks.