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Databricks Databricks-Certified-Data-Engineer-Associate Exam With Confidence Using Practice Dumps

Exam Code:
Databricks-Certified-Data-Engineer-Associate
Exam Name:
Databricks Certified Data Engineer Associate Exam
Certification:
Databricks Certification
Vendor:
Databricks
Questions:
230
Last Updated:
Aug 14, 2026
Exam Status:
Stable
Databricks Databricks-Certified-Data-Engineer-Associate

Databricks-Certified-Data-Engineer-Associate: Databricks Certification Exam 2025 Study Guide Pdf and Test Engine

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Databricks Certified Data Engineer Associate Exam Questions and Answers

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Question 1

A data engineer has two DataFrames:

    orders_df, containing all customer orders

    customers_df, containing only active customers

The engineer needs to remove all orders placed by inactive customers.

Which operation achieves this requirement?

Options:

A.

Perform a left join from customers_df to orders_df.

B.

Perform a cross join between orders_df and customers_df.

C.

Perform a left join from orders_df to customers_df.

D.

Perform an inner join between orders_df and customers_df using the customer identifier.

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Question 2

A data engineer is processing ingested streaming tables and needs to filter out NULL values in the order_datetime column from the raw streaming table orders_raw and store the results in a new table orders_valid using DLT.

Which code snippet should the data engineer use?

A)

B)

C)

D)

Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D

Question 3

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?

Options:

A.

region_sales = sales_df.groupBy( " region " ).agg(sum( " sales_amountM).alias( " total_sales_amount " ))

B.

region_sales = sales_df. sum ( " salen_aiTiount " ) . groupBy ( " region " ) .alias ( " total_sale3_amount " )

C.

region_sales= sales_df.groupBy( " category " ).sum(nsales_amount " ).alias( " t_otal_sales_amounl " )

D.

region sales - sales_df.agg(sum( " sales_amount " ).groupBy( " region " ).alias( " total sales amount " ))

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