Databricks DATABRICKS-CERTIFIED-DATA-ENGINEER-ASSOCIATE Online Practice Questions and Exam Preparation

Databricks DATABRICKS-CERTIFIED-DATA-ENGINEER-ASSOCIATE Online Questions & Answers

• Question 1:

  A data engineer needs to provide access to a group named manufacturing-team. The team needs privileges to create tables in the quality schema.

  Which set of SQL commands will grant a group named manufacturing-team to create tables in a schema named production with the parent catalog named manufacturing with the least privileges?

  A. GRANT CREATE TABLE ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT USE SCHEMA ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT USE CATALOG ON CATALOG manufacturing TO manufacturing-team;
  B. GRANT USE TABLE ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT USE SCHEMA ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT USE CATALOG ON CATALOG manufacturing TO manufacturing-team;
  C. GRANT CREATE TABLE ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT CREATE SCHEMA ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT CREATE CATALOG ON CATALOG manufacturing TO manufacturing-team;
  D. GRANT CREATE TABLE ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT CREATE SCHEMA ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT USE CATALOG ON CATALOG manufacturing TO manufacturing-team;
  A. GRANT CREATE TABLE ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT USE SCHEMA ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT USE CATALOG ON CATALOG manufacturing TO manufacturing-team;

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  explanation:

  Explanation

  To allow a group to create tables in a schema with least privileges, they need:

  GRANT CREATE TABLE on the schema GRANT USE SCHEMA on the schema GRANT USE CATALOG on the parent catalog This ensures proper access without granting unnecessary privileges like creating schemas or catalogs.

• Question 2:

  A data engineer at a company that uses Databricks with Unity Catalog needs to share a collection of tables with an external partner who also uses a Databricks workspace enabled for Unity Catalog. The data engineer decides to use Delta Sharing to accomplish this.

  What is the first piece of information the data engineer should request from the external partner to set up Delta Sharing?

  A. The IP address of their Databricks workspace
  B. The name of their Databricks cluster
  C. The sharing identifier of their Unity Catalog metastore
  D. Their Databricks account password
  C. The sharing identifier of their Unity Catalog metastore

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  explanation:

  Explanation

  To configure Delta Sharing between two Databricks workspaces with Unity Catalog, the first requirement is the sharing identifier of the partner's Unity Catalog metastore, which enables secure setup of the share and recipient relationship.

• Question 3:

  A company is collaborating with a partner that does not use Databricks but needs access to a large historical dataset stored in Delta format. The data engineer needs to ensure that the partner can access the data securely, without the need for them to set up an account, and with read-only access.

  How should the data be shared?

  A. Share the dataset by exporting it to a CSV file and manually transferring the file to the partner's system.
  B. Grant your partner access to your Databricks workspace and assign them full write permissions to the Delta table, enabling them to modify the dataset.
  C. Share the dataset using Unity Catalog, ensuring that both teams have full write access to the data within the same organization.
  D. Share the dataset using Delta Sharing, which allows your partner to access the data using a secure, read-only URL without requiring a Databricks account, ensuring that they cannot modify the data.
  D. Share the dataset using Delta Sharing, which allows your partner to access the data using a secure, read-only URL without requiring a Databricks account, ensuring that they cannot modify the data.

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  explanation:

  Explanation

  Delta Sharing provides secure, read-only access to Delta tables via a sharing protocol, allowing partners without a Databricks account to query the data through a secure URL while ensuring they cannot modify it.

• Question 4:

  A data engineer is configuring Unity Catalog in Databricks and needs to assign a role to a user who should have the ability to grant and revoke privileges on various data objects within a specific schema, but should not have read/write access over the schema or its objects.

  Which role should the data engineer assign to this user?

  A. Table Owner
  B. Catalog Owner
  C. Schema Owner
  D. USE catalog/schema privilege on the schema
  C. Schema Owner

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  explanation:

  Explanation

  The Schema Owner role in Unity Catalog allows a user to grant and revoke privileges on data objects within the schema without requiring read/write access to the schema's data itself, fitting the requirement.

• Question 5:

  A data engineer is managing a data pipeline in Databricks, where multiple Delta tables are used for various transformations. The team wants to track how data flows through the pipeline, including identifying dependencies between Delta tables, notebooks, jobs, and dashboards. The data engineer is utilizing the Unity Catalog lineage feature to monitor this process.

  How does Unity Catalog's data lineage feature support the visualization of relationships between Delta tables, notebooks, jobs, and dashboards?

  A. Unity Catalog lineage visualizes dependencies between Delta tables, notebooks, and jobs, but does not provide column-level tracing or relationships with dashboards.
  B. Unity Catalog lineage only supports visualizing relationships at the table level and does not extend to notebooks, jobs, or dashboards.
  C. Unity Catalog lineage provides an interactive graph that tracks dependencies between tables and notebooks but excludes any job-related dependencies or dashboard visualizations.
  D. Unity Catalog provides an interactive graph that visualizes the dependencies between Delta tables, notebooks, jobs, and dashboards, while also supporting column-level tracking of data transformations.
  B. Unity Catalog lineage only supports visualizing relationships at the table level and does not extend to notebooks, jobs, or dashboards.

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  explanation:

  Explanation

  Unity Catalog lineage provides an interactive graph that shows how data flows across Delta tables, notebooks, jobs, and dashboards, with column-level lineage to trace transformations precisely for governance and auditing.

• Question 6:

  A data engineer is reviewing the documentation on audit logs in Databricks for compliance purposes and needs to understand the format in which audit logs output events. How are events formatted in Databricks audit logs?

  A. In Databricks, audit logs output events in a JSON format.
  B. In Databricks, audit logs output events in a CSV format.
  C. In Databricks, audit logs output events in an XML format.
  D. In Databricks, audit logs output events in a plain text format.
  A. In Databricks, audit logs output events in a JSON format.

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  explanation:

  Explanation

  Databricks audit logs output events in JSON format, which provides structured, machine-readable data suitable for compliance monitoring and integration with security tools.

• Question 7:

  An organization needs to share a dataset stored in its Databricks Unity Catalog with an external partner who uses a different data platform that is not Databricks. The goal is to maintain data security and ensure the partner can access the

  data efficiently.

  .

  Which method should the data engineer use to securely share the dataset with the external partner?

  A. Using Delta Sharing with the open sharing protocol
  B. Exporting data as CSV files and emailing them
  C. Using a third-party API to access the Delta table
  D. Databricks-to-Databricks Sharing
  A. Using Delta Sharing with the open sharing protocol

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  explanation:

  Explanation

  Delta Sharing with the open sharing protocol allows secure data sharing from Unity Catalog to external partners, even if they are not using Databricks, while maintaining governance and efficient access.

• Question 8:

  An organization has data stored across multiple external systems, including MySQL, Amazon Redshift, and Google BigQuery. The data engineer wants to perform analytics without ingesting directly into Databricks, ensuring unified governance and minimizing data duplication.

  Which feature of Databricks enables querying these external data sources while maintaining centralized governance?

  A. Delta Lake
  B. Lakehouse Federation
  C. MLflow
  D. Databricks Connect
  B. Lakehouse Federation

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  explanation:

  Explanation

  Lakehouse Federation allows Databricks to query external data sources like MySQL, Redshift, and BigQuery without moving or duplicating data, while maintaining centralized governance through Unity Catalog.

• Question 9:

  A company uses Delta Sharing to collaborate with partners across different cloud providers and geographic regions. What will result in additional costs due to cross-region or egress fees?

  A. Sharing data within the same cloud provider and region
  B. Transferring data via Delta Sharing across clouds and across different geographic regions
  C. Accessing Delta Sharing data using a VPN within the same data center
  D. Utilizing Delta Sharing for internal data analytics within a single cloud environment
  B. Transferring data via Delta Sharing across clouds and across different geographic regions

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  explanation:

  Explanation

  Transferring data via Delta Sharing across clouds and across different geographic regions incurs additional costs because cloud providers charge cross-region and egress fees when data leaves a region or moves between providers.

• Question 10:

  A Databricks single-task workflow fails at the last task due to an error in a notebook. The data engineer fixes the mistake in the notebook. What should the data engineer do to rerun the workflow?

  A. Repair the task
  B. Rerun the pipeline
  C. Restart the cluster
  D. Switch the cluster
  A. Repair the task

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  explanation:

  Explanation

  For a single-task workflow, the correct action is to repair the task, which reruns only the failed task after fixing the error, avoiding unnecessary re-execution of the whole workflow.