Most Recent Databricks-Certified-Data-Engineer-Associate Exam Dumps

Prepare for the Databricks Certified Data Engineer Associate Exam exam with our extensive collection of questions and answers. These practice Q&A are updated according to the latest syllabus, providing you with the tools needed to review and test your knowledge.

QA4Exam focus on the latest syllabus and exam objectives, our practice Q&A are designed to help you identify key topics and solidify your understanding. By focusing on the core curriculum, These Questions & Answers helps you cover all the essential topics, ensuring you're well-prepared for every section of the exam. Each question comes with a detailed explanation, offering valuable insights and helping you to learn from your mistakes. Whether you're looking to assess your progress or dive deeper into complex topics, our updated Q&A will provide the support you need to confidently approach the Databricks-Certified-Data-Engineer-Associate exam and achieve success.

The questions for Databricks-Certified-Data-Engineer-Associate were last updated on Mar 31, 2025.

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Question No. 1

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?

AParquet files can be partitioned

BCREATE TABLE AS SELECT statements cannot be used on files

CParquet files have a well-defined schema

DParquet files have the ability to be optimized

EParquet files will become Delta tables

Show Answer

Correct Answer: C

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.

Question No. 2

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?

ADatabricks account representative

BThis transfer is not possible

CWorkspace administrator

DNew lead data engineer

EOriginal data engineer

Show Answer

Correct Answer: C

The workspace administrator is the only individual who can transfer ownership of the Delta tables in Data Explorer, assuming the original data engineer no longer has access. The workspace administrator has the highest level of permissions in the workspace and can manage all resources, users, and groups. The other options are either not possible or not sufficient to perform the ownership transfer. The Databricks account representative is not involved in the workspace management. The transfer is possible and not dependent on the original data engineer. The new lead data engineer may not have the necessary permissions to access or modify the Delta tables, unless granted by the workspace administrator or the original data engineer before leaving.Reference:Workspace access control,Manage Unity Catalog object ownership.

Question No. 3

A new data engineering team team has been assigned to an ELT project. The new data engineering team will need full privileges on the table sales to fully manage the project.

Which command can be used to grant full permissions on the database to the new data engineering team?

Agrant all privileges on table sales TO team;

BGRANT SELECT ON TABLE sales TO team;

CGRANT SELECT CREATE MODIFY ON TABLE sales TO team;

DGRANT ALL PRIVILEGES ON TABLE team TO sales;

Show Answer

Correct Answer: A

To grant full privileges on a table such as 'sales' to a group like 'team', the correct SQL command in Databricks is:

GRANT ALL PRIVILEGES ON TABLE sales TO team;

This command assigns all available privileges, including SELECT, INSERT, UPDATE, DELETE, and any other data manipulation or definition actions, to the specified team. This is typically necessary when a team needs full control over a table to manage and manipulate it as part of a project or ongoing maintenance.

Reference: Databricks documentation on SQL permissions: SQL Permissions in Databricks

Question No. 4

A data engineering team has two tables. The first table march_transactions is a collection of all retail transactions in the month of March. The second table april_transactions is a collection of all retail transactions in the month of April. There are no duplicate records between the tables.

Which of the following commands should be run to create a new table all_transactions that contains all records from march_transactions and april_transactions without duplicate records?

ACREATE TABLE all_transactions AS
SELECT * FROM march_transactions
INNER JOIN SELECT * FROM april_transactions;

BCREATE TABLE all_transactions AS
SELECT * FROM march_transactions
UNION SELECT * FROM april_transactions;

CCREATE TABLE all_transactions AS
SELECT * FROM march_transactions
OUTER JOIN SELECT * FROM april_transactions;

DCREATE TABLE all_transactions AS
SELECT * FROM march_transactions
INTERSECT SELECT * from april_transactions;

ECREATE TABLE all_transactions AS
SELECT * FROM march_transactions
MERGE SELECT * FROM april_transactions;

Show Answer

Correct Answer: B

The correct command to create a new table that contains all records from two tables without duplicate records is to use theUNIONoperator. The UNION operator combines the results of two queries and removes any duplicate rows. The INNER JOIN, OUTER JOIN, and MERGE operators do not remove duplicate rows, and the INTERSECT operator only returns the rows that are common to both tables. Therefore, option B is the only correct answer.Reference:Databricks SQL Reference - UNION,Databricks SQL Reference - JOIN,Databricks SQL Reference - MERGE, [Databricks SQL Reference - INTERSECT]

Question No. 5

A data engineer has joined an existing project and they see the following query in the project repository:

CREATE STREAMING LIVE TABLE loyal_customers AS

SELECT customer_id -

FROM STREAM(LIVE.customers)

WHERE loyalty_level = 'high';

Which of the following describes why the STREAM function is included in the query?

AThe STREAM function is not needed and will cause an error.

BThe table being created is a live table.

CThe customers table is a streaming live table.

DThe customers table is a reference to a Structured Streaming query on a PySpark DataFrame.

EThe data in the customers table has been updated since its last run.

Show Answer

Correct Answer: C

The STREAM function is used to process data from a streaming live table or view, which is a table or view that contains data that has been added only since the last pipeline update. Streaming live tables and views are stateful, meaning that they retain the state of the previous pipeline run and only process new data based on the current query. This is useful for incremental processing of streaming or batch data sources. The customers table in the query is a streaming live table, which means that it contains the latest data from the source. The STREAM function enables the query to read the data from the customers table incrementally and create another streaming live table named loyal_customers, which contains the customer IDs of the customers with high loyalty level.Reference:Difference between LIVE TABLE and STREAMING LIVE TABLE,CREATE STREAMING TABLE,Load data using streaming tables in Databricks SQL.

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