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Data Analyst Databricks Certified Data Analyst Associate Exam

Databricks Certified Data Analyst Associate Exam

Last Update Jul 25, 2026
Total Questions : 118

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Questions 2

A Data Analyst is working on employees_df and needs to add a new column where a 10% tax is calculated on the salary. Additionally, the DataFrame contains the column age, which is not needed.

Which code fragment adds the tax column and removes the age column?

Options:

employees_df = employees_df.withColumn( " tax " , employees_df.salary * 10).dropField( " age " )

employees_df = employees_df.withColumn( " tax " , employees_df.salary * 0.1).drop( " age " )

employees_df = employees_df.withColumn( " tax " , lit(0.1) * col( " salary " )).dropField( " age " )

employees_df = employees_df.withColumn( " tax " , employees_df.salary * 10).drop( " age " )

Discussion 0

Questions 3

A data analyst has a managed table table_name in database database_name. They would now like to remove the table from the database and all of the data files associated with the table. The rest of the tables in the database must continue to exist.

Which of the following commands can the analyst use to complete the task without producing an error?

Options:

DROP DATABASE database_name;

DROP TABLE database_name.table_name;

DELETE TABLE database_name.table_name;

DELETE TABLE table_name FROM database_name;

DROP TABLE table_name FROM database_name;

Discussion 0

Questions 4

Data engineers and data analysts are working together on a data pipeline. The data engineer is working on the raw, bronze, and silver layers of the pipeline using Python, and the data analyst is working on the gold layer of the pipeline using SQL. The raw source of the pipeline is a streaming input. They now want to migrate their pipeline to use Delta Live Tables.

Which of the following changes will need to be made to the pipeline when migrating to Delta Live Tables?

Options:

The pipeline can have different notebook sources in SQL and Python.

The pipeline will need to be written entirely in SQL.

The pipeline will need to use a batch source in place of a streaming source.

The pipeline will need to be written entirely in Python.

Discussion 0

Questions 5

A data analyst has been asked to use the below table sales_table to rank products within region by the sales.

Input table:

region product sales

WEST A 1880.59

EAST A 2045.99

EAST B 4583.23

WEST B 3391.19

The result of the query should look like this:

region product rank

EAST B 1

EAST A 2

WEST B 1

WEST A 2

Which query will accomplish this task?

Options:

SELECT region, product, RANK() OVER ( ORDER BY sales DESC ) AS rankFROM sales_table;

SELECT region, product, RANK() OVER ( PARTITION BY product ORDER BY sales DESC ) AS rankFROM sales_table;

SELECT region, product, RANK() OVER ( PARTITION BY region ) AS rankFROM sales_table;

SELECT region, product, RANK() OVER ( PARTITION BY region ORDER BY sales DESC ) AS rankFROM sales_table;

Option A

Option B

Option C

Discussion 0

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