Actual Dumps for Databricks Databricks Certified Data Analyst Associate Exam 2026

Question No: 1

MultipleChoice

Which of the following describes how Databricks SQL should be used in relation to other business intelligence (BI) tools like Tableau, Power BI, and looker?

Options

AAs an exact substitute with the same level of functionality

BAs a substitute with less functionality

CAs a complete replacement with additional functionality

DAs a complementary tool for professional-grade presentations

EAs a complementary tool for quick in-platform Bl work
Databricks SQL is not meant to replace or substitute other BI tools, but rather to complement them by providing a fast and easy way to query, explore, and visualize data on the lakehouse using the built-in SQL editor, visualizations, and dashboards. Databricks SQL also integrates seamlessly with popular BI tools like Tableau, Power BI, and Looker, allowing analysts to use their preferred tools to access data through Databricks clusters and SQL warehouses. Databricks SQL offers low-code and no-code experiences, as well as optimized connectors and serverless compute, to enhance the productivity and performance of BI workloads on the lakehouse.Reference:Databricks SQL,Connecting Applications and BI Tools to Databricks SQL,Databricks integrations overview,Databricks SQL: Delivering a Production SQL Development Experience on the Lakehouse

Question No: 2

MultipleChoice

Where in the Databricks SQL workspace can a data analyst configure a refresh schedule for a query when the query is not attached to a dashboard or alert?

Options

AData bxplorer

BThe Visualization editor

CThe Query Editor

DThe Dashboard Editor
In Databricks SQL, to configure a refresh schedule for a query that is not attached to a dashboard or alert, a data analyst should use the Query Editor. Within the Query Editor, there is an option to set up scheduled executions for queries. This feature enables the query to run at specified intervals, ensuring that the results are updated regularly. By scheduling queries in this manner, analysts can automate data refreshes and maintain up-to-date query results without manual intervention.

Question No: 3

MultipleChoice

A data engineer is working with a nested array column products in table transactions. They want to expand the table so each unique item in products for each row has its own row where the transaction_id column is duplicated as necessary.

They are using the following incomplete command:

Which option best lines of code can they use to fill in the blank in the above code block so that it successfully completes the task?

Options

Aarray distinct(produces)

Bexplode(produces)

Creduce(produces)

Darray(produces)

Eflatten(produces)
Theexplodefunction is used to transform a DataFrame column of arrays or maps into multiple rows, duplicating the other column's values. In this context, it will be used to expand the nested array column products in the transactions table so that each unique item in products for each row has its own row and the transaction_id column is duplicated as necessary.Reference:Databricks Documentation
I also noticed that you sent me an image along with your message. The image shows a snippet of SQL code that is incomplete. It begins with ''SELECT'' indicating a query to retrieve data. ''transaction_id,'' suggests that transaction_id is one of the columns being selected. There are blanks indicated by underscores where certain parts of the SQL command should be, including what appears to be an alias for a column and part of the FROM clause. The query ends with ''FROM transactions;'' indicating data is being selected from a 'transactions' table.
If you are interested in learning more about Databricks Data Analyst Associate certification, you can check out the following resources:
Databricks Certified Data Analyst Associate: This is the official page for the certification exam, where you can find the exam guide, registration details, and preparation tips.
Data Analysis With Databricks SQL: This is a self-paced course that covers the topics and skills required for the certification exam. You can access it for free on Databricks Academy.
Tips for the Databricks Certified Data Analyst Associate Certification: This is a blog post that provides some useful advice and study tips for passing the certification exam.
Databricks Certified Data Analyst Associate Certification: This is another blog post that gives an overview of the certification exam and its benefits.

Question No: 4

MultipleChoice

Which location can be used to determine the owner of a managed table?

Options

AReview the Owner field in the table page using Catalog Explorer

BReview the Owner field in the database page using Data Explorer

CReview the Owner field in the schema page using Data Explorer

DReview the Owner field in the table page using the SQL Editor
In Databricks, to determine the owner of a managed table, you can utilize the Catalog Explorer feature. The steps are as follows:
Access Catalog Explorer:
In your Databricks workspace, click on the Catalog icon in the sidebar to open Catalog Explorer.
Navigate to the Table:
Within Catalog Explorer, browse through the catalog and schema to locate the specific managed table whose ownership you wish to verify.
View Table Details:
Click on the table name to open its details page.
Identify the Owner:
On the table's details page, review the Owner field, which displays the principal (user, service principal, or group) that owns the table.
This method provides a straightforward way to ascertain the ownership of managed tables within the Databricks environment. Understanding table ownership is essential for managing permissions and ensuring proper access control.

Question No: 5

MultipleChoice

A data analyst is processing a complex aggregation on a table with zero null values and their query returns the following result:

Which of the following queries did the analyst run to obtain the above result?

Options

AOption A

BOption B

COption C

DOption D

EOption E
The result set provided shows a combination of grouping by two columns (group_1 and group_2) with subtotals for each level of grouping and a grand total. This pattern is typical of a GROUP BY ... WITH ROLLUP operation in SQL, which provides subtotal rows and a grand total row in the result set.
Considering the query options:
A) Option A: GROUP BY group_1, group_2 INCLUDING NULL - This is not a standard SQL clause and would not result in subtotals and a grand total.
B) Option B: GROUP BY group_1, group_2 WITH ROLLUP - This would create subtotals for each unique group_1, each combination of group_1 and group_2, and a grand total, which matches the result set provided.
C) Option C: GROUP BY group_1, group 2 - This is a simple GROUP BY and would not include subtotals or a grand total.
D) Option D: GROUP BY group_1, group_2, (group_1, group_2) - This syntax is not standard and would likely result in an error or be interpreted as a simple GROUP BY, not providing the subtotals and grand total.
E) Option E: GROUP BY group_1, group_2 WITH CUBE - The WITH CUBE operation produces subtotals for all combinations of the selected columns and a grand total, which is more than what is shown in the result set.
The correct answer is Option B, which uses WITH ROLLUP to generate the subtotals for each level of grouping as well as a grand total. This matches the result set where we have subtotals for each group_1, each combination of group_1 and group_2, and the grand total where both group_1 and group_2 are NULL.

Question No: 6

MultipleChoice

A data analyst wants the following output:

customer_name number_of_orders

John Doe 388

Zhang San 234

Which statement will produce this output?

Options

ASELECT customer_name, count(order_id) AS number_of_orders
FROM customers
JOIN orders
ON customers.customer_id = orders.customer_id
GROUP BY customer_name;

BSELECT customer_name, count(order_id) number_of_orders
FROM customers
JOIN orders
ON customers.customer_id = orders.customer_id USE customer_name;

CSELECT customerjiame, (order_id) number_of_orders
FROM customers
JOIN orders
ON customers.customer_id = orders.customer_id;

DSELECT customerjiame, count(order_id)
FROM customers
JOIN orders
ON customers.customer_id = orders.customer_id GROUP BY customerjiame;

Question No: 7

MultipleChoice

A data analyst is processing a complex aggregation on a table with zero null values and the query returns the following result:

Which query did the analyst execute in order to get this result?

Options

AOption A

BOption B

COption C

DOption D

Free Databricks Certified Data Analyst Associate Exam Dumps August 2026