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The GAQM Databricks-Certified-Data-Engineer-Associate (Databricks Certified Data Engineer Associate) Certification Exam is designed to validate the skills and knowledge of data engineers who work with the Databricks Unified Analytics Platform. Databricks Certified Data Engineer Associate Exam certification is ideal for professionals who want to demonstrate their expertise in building and optimizing data pipelines, data transformation, and data storage using Databricks.

Databricks Certified Data Engineer Associate Exam Sample Questions (Q32-Q37):

NEW QUESTION # 32
A data engineering team is designing the Gold layer in their Unity Catalog-governed lakehouse for downstream BI and analytics users. The team wants to expose business-ready metrics with fast query performance and consistent definitions, while keeping the transformation logic in Spark notebooks. Which type of Gold layer object meets this requirement?

Answer: B

Explanation:
A materialized view stores precomputed Gold-layer aggregations, providing BI tools with fast queries and centrally defined, consistent business results while allowing the transformation logic to remain in Databricks notebooks.


NEW QUESTION # 33
A data engineer wants to create a new table containing the names of customers who live in France.
They have written the following command:
CREATE TABLE customersInFrance
_____ AS
SELECT id,
firstName,
lastName
FROM customerLocations
WHERE country = 'FRANCE';
A senior data engineer mentions that it is organization policy to include a table property indicating that the new table includes personally identifiable information (Pll).
Which line of code fills in the above blank to successfully complete the task?

Answer: D

Explanation:
To include a property indicating that a table contains personally identifiable information (PII), the TBLPROPERTIES keyword is used in SQL to add metadata to a table. The correct syntax to define a table property for PII is as follows:
CREATE TABLE customersInFrance
USING DELTA
TBLPROPERTIES ('PII' = 'true')
AS
SELECT id,
firstName,
lastName
FROM customerLocations
WHERE country = 'FRANCE';
The TBLPROPERTIES ('PII' = 'true') line correctly sets a table property that tags the table as containing personally identifiable information. This is in accordance with organizational policies for handling sensitive information.


NEW QUESTION # 34
Which of the following describes a benefit of creating an external table from Parquet rather than CSV when using a CREATE TABLE AS SELECT statement?

Answer: C

Explanation:
Option C is the correct answer because Parquet files have a well-defined schema that is embedded within the data itself. This means that the data types and column names of the Parquet files are automatically detected and preserved when creating an external table from them. This also enables the use of SQL and other structured query languages to access and analyze the data. CSV files, on the other hand, do not have a schema embedded in them, and require specifying the schema explicitly or inferring it from the data when creating an external table from them. This can lead to errors or inconsistencies in the data types and column names, and also increase the processing time and complexity.
References: CREATE TABLE AS SELECT, Parquet Files, CSV Files, Parquet vs. CSV


NEW QUESTION # 35
A data engineer is attempting to grant a user access to a view. They successfully run the following command:
GRANT SELECT ON VIEW sales_catalog.market_data.summary
TO analyst_group;
However, the analyst still receives an "Insufficient Permissions" error when trying to query the view.
In which order should the engineer verify the hierarchy of securable objects to ensure that the analyst has the necessary usage permissions?

Answer: A


NEW QUESTION # 36
A data engineer has configured a Structured Streaming job to read from a table, manipulate the data, and then perform a streaming write into a new table.
The cade block used by the data engineer is below:

If the data engineer only wants the query to execute a micro-batch to process data every 5 seconds, which of the following lines of code should the data engineer use to fill in the blank?

Answer: D

Explanation:
The processingTime option specifies a time-based trigger interval for fixed interval micro-batches. This means that the query will execute a micro-batch to process data every 5 seconds, regardless of how much data is available. This option is suitable for near-real time processing workloads that require low latency and consistent processing frequency. The other options are either invalid syntax (A, C), default behavior (B), or experimental feature (E). References: Databricks Documentation - Configure Structured Streaming trigger intervals, Databricks Documentation - Trigger.


NEW QUESTION # 37
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