Databricks-Certified-Data-Engineer-Associate Test Guide - Databricks Certified Data Engineer Associate Exam Study Question & Databricks-Certified-Data-Engineer-Associate Exam Questions

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Databricks Databricks-Certified-Data-Engineer-Associate Exam Syllabus Topics:

Section	Objectives
Databricks Lakehouse Platform Fundamentals	- Clusters, notebooks, and basic Databricks environment usage - Workspace, architecture, and core platform concepts
Data Processing and Transformations	- User-defined functions (UDFs) - Apache Spark SQL operations (joins, aggregations, filtering) - PySpark DataFrame transformations - Delta Lake fundamentals (tables, transactions, optimization)
Data Ingestion and ELT Development	- Handling structured and semi-structured data - ETL patterns and transformations - Data ingestion using Spark SQL and PySpark
Data Governance and Quality	- Data access control and governance - Data quality concepts and management - Unity Catalog basics
Productionizing Data Pipelines	- Scheduling and monitoring jobs - Pipeline deployment and operationalization - Databricks Workflows / Jobs orchestration

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q296-Q301):

NEW QUESTION # 296
A data engineer is attempting to grant a user access to a view. They successfully run 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 the analyst has the necessary usage permissions?

A. WORKSPACE -> CLUSTER -> VIEW
B. METASTORE -> TABLE -> VIEW
C. STORAGE CREDENTIAL -> EXTERNAL LOCATION -> VIEW
D. CATALOG -> SCHEMA -> VIEW

Answer: D

Explanation:
To query the view, the analyst needs USE CATALOG on sales_catalog, then USE SCHEMA on market_data, and SELECT on summary. Privileges on the underlying tables are not required for querying a Unity Catalog view.

NEW QUESTION # 297
A data engineer is getting a partner organization up to speed with Databricks account. Both teams share some business use cases. The data engineer has to share some of your Unity-Catalog managed delta tables and the notebook jobs creating those tables with the partner organization.
How can the data engineer seamlessly share the required information?

A. Data and Notebooks can be shared simply using Unity Catalog.
B. Share required datasets and notebooks via Delta Sharing. Manage permissions via Unity Catalog.
C. Share access to codebase via Github and allow them to ingest datasets from your Datalake.
D. Zip all the code and share via email and allow data ingestion from your data lake

Answer: B

NEW QUESTION # 298

Calculate the total sales amount for each region and store the results in a new dataframe called region_sales.
Given the expected result:

Which code will generate the expected result?

A. region sales - sales_df.agg(sum("sales_amount").groupBy("region").alias("total sales amount"))
B. region_sales = sales_df. sum ("salen_aiTiount") . groupBy ("region") .alias ("total_sale3_amount")
C. region_sales = sales_df.groupBy("region").agg(sum("sales_amountM).alias("total_sales_amount"))
D. region_sales= sales_df.groupBy("category").sum(nsales_amount").alias("t_otal_sales_amounl")

Answer: C

NEW QUESTION # 299
A data engineer needs to create a table in Databricks using data from their organization's existing SQLite database.
They run the following command:

Which of the following lines of code fills in the above blank to successfully complete the task?

A. org.apache.spark.sql.jdbc
B. autoloader
C. sqlite
D. DELTA
E. org.apache.spark.sql.sqlite

Answer: A

Explanation:
CREATE TABLE new_employees_table
USING JDBC
OPTIONS (
url "<jdbc_url>",
dbtable "<table_name>",
user '<username>',
password '<password>'
) AS
SELECT * FROM employees_table_vw
https://docs.databricks.com/external-data/jdbc.html#language-sql

NEW QUESTION # 300
A data engineer is working with two tables. Each of these tables is displayed below in its entirety.

The data engineer runs the following query to join these tables together:

Which of the following will be returned by the above query?

A. Option A
B. Option E
C. Option B
D. Option D
E. Option C

Answer: A

Explanation:
Option A is the correct answer because it shows the result of an INNER JOIN between the two tables. An INNER JOIN returns only the rows that have matching values in both tables based on the join condition. In this case, the join condition is ON a.customer_id = c.customer_id, which means that only the rows that have the same customer ID in both tables will be included in the output. The output will have four columns: customer_id, name, account_id, and overdraft_amt. The output will have four rows, corresponding to the four customers who have accounts in the account table.
The use of INNER JOIN can be referenced from Databricks documentation on SQL JOIN or from other sources like W3Schools or GeeksforGeeks.

NEW QUESTION # 301
......

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