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Databricks Certified Data Engineer Associate Exam Sample Questions (Q276-Q281):

NEW QUESTION # 276
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?

A. "COMMENT PII"
B. PII
C. COMMENT "Contains PII"
D. There is no way to indicate whether a table contains PII.
E. TBLPROPERTIES PII

Answer: C

Explanation:
In Databricks, when creating a table, you can add a comment to columns or the entire table to provide more information about the data it contains. In this case, since it's organization policy to indicate that the new table includes personally identifiable information (PII), option D is correct. The line of code would be added after defining the table structure and before closing with a semicolon. Reference: Data Engineer Associate Exam Guide, CREATE TABLE USING (Databricks SQL)

NEW QUESTION # 277
A data engineer needs to ingest JSON change data from Salesforce into Unity Catalog-governed Delta tables with a low-code, fully managed experience. Which Databricks capability should the data engineer use?

A. Auto Loader reading JSON files from an S3 bucket exported by Salesforce
B. A Lakeflow Connect managed Salesforce connector that writes into Unity Catalog Delta tables
C. Use the Salesforce REST API in a PySpark notebook to query changed records and write them to Delta tables
D. Auto Loader with a file arrival trigger on DBFS

Answer: B

Explanation:
Lakeflow Connect's managed Salesforce connector provides a low-code, fully managed ingestion pipeline that incrementally loads Salesforce data into Unity Catalog-governed Delta tables.

NEW QUESTION # 278
A data engineer has left the organization. The data team needs to transfer ownership of the data engineer's Delta tables to a new data engineer. The new data engineer is the lead engineer on the data team.
Assuming the original data engineer no longer has access, which of the following individuals must be the one to transfer ownership of the Delta tables in Data Explorer?

A. This transfer is not possible
B. Databricks account representative
C. Original data engineer
D. New lead data engineer
E. Workspace administrator

Answer: E

NEW QUESTION # 279
Which of the following describes a scenario in which a data team will want to utilize cluster pools?

A. An automated report needs to be runnable by all stakeholders.
B. An automated report needs to be tested to identify errors.
C. An automated report needs to be made reproducible.
D. An automated report needs to be refreshed as quickly as possible.
E. An automated report needs to be version-controlled across multiple collaborators.

Answer: D

Explanation:
Explanation
Cluster pools are typically used in distributed computing environments, such as cloud-based data platforms like Databricks. They allow you to pre-allocate a set of compute resources (a cluster) for specific tasks or workloads. In this case, if an automated report needs to be refreshed as quickly as possible, you can allocate a cluster pool with sufficient resources to ensure fast data processing and report generation. This helps ensure that the report is generated with minimal latency and can be delivered to stakeholders in a timely manner.
Cluster pools allow you to optimize resource allocation for high-demand, time-sensitive tasks like real-time report generation.

NEW QUESTION # 280
What is the functionality of AutoLoader in Databricks?

A. Auto Loader automatically ingests and processes new files from cloud storage, handling both batch and streaming data with support for schema evolution.
B. Auto Loader automatically ingests and processes new files from cloud storage, handling only streaming data with no support for schema evolution.
C. Auto Loader automatically ingests and processes new files from cloud storage, handling batch data with support for schema evolution.
D. Auto Loader automatically ingests and processes new files from cloud storage, handling batch and streaming data with no support for schema evolution.

Answer: A

Explanation:
Auto Loader in Databricks automatically ingests new files from cloud storage, supports both batch and streaming ingestion, and handles schema evolution, making it ideal for scalable pipelines.

NEW QUESTION # 281
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