Databricks Databricks-Certified-Data-Analyst-Associate Daily Practice Exam New 2025 Updated 67 Questions [Q32-Q52]

July 1, 2025 admin 0 Comments

Rate this post

Databricks Databricks-Certified-Data-Analyst-Associate Daily Practice Exam New 2025 Updated 67 Questions

Use Valid Databricks-Certified-Data-Analyst-Associate Exam – Actual Exam Question & Answer

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

Topic	Details
Topic 1	Data Visualization and Dashboarding: Sub-topics of this topic are about of describing how notifications are sent, how to configure and troubleshoot a basic alert, how to configure a refresh schedule, the pros and cons of sharing dashboards, how query parameters change the output, and how to change the colors of all of the visualizations. It also discusses customized data visualizations, visualization formatting, Query Based Dropdown List, and the method for sharing a dashboard.
Topic 2	Data Management: The topic describes Delta Lake as a tool for managing data files, Delta Lake manages table metadata, benefits of Delta Lake within the Lakehouse, tables on Databricks, a table owner’s responsibilities, and the persistence of data. It also identifies management of a table, usage of Data Explorer by a table owner, and organization-specific considerations of PII data. Lastly, the topic it explains how the LOCATION keyword changes, usage of Data Explorer to secure data.
Topic 3	Analytics applications: It describes key moments of statistical distributions, data enhancement, and the blending of data between two source applications. Moroever, the topic also explains last-mile ETL, a scenario in which data blending would be beneficial, key statistical measures, descriptive statistics, and discrete and continuous statistics.
Topic 4	SQL in the Lakehouse: It identifies a query that retrieves data from the database, the output of a SELECT query, a benefit of having ANSI SQL, access, and clean silver-level data. It also compares and contrasts MERGE INTO, INSERT TABLE, and COPY INTO. Lastly, this topic focuses on creating and applying UDFs in common scaling scenarios.
Topic 5	Databricks SQL: This topic discusses key and side audiences, users, Databricks SQL benefits, complementing a basic Databricks SQL query, schema browser, Databricks SQL dashboards, and the purpose of Databricks SQL endpoints warehouses. Furthermore, the delves into Serverless Databricks SQL endpoint warehouses, trade-off between cluster size and cost for Databricks SQL endpoints warehouses, and Partner Connect. Lastly it discusses small-file upload, connecting Databricks SQL to visualization tools, the medallion architecture, the gold layer, and the benefits of working with streaming data.

NEW QUESTION 32
Consider the following two statements:
Statement 1:

Statement 2:

Which of the following describes how the result sets will differ for each statement when they are run in Databricks SQL?

The first statement will return all data from the customers table and matching data from the orders table. The second statement will return all data from the orders table and matching data from the customers table. Any missing data will be filled in with NULL.

When the first statement is run, only rows from the customers table that have at least one match with the orders table on customer_id will be returned. When the second statement is run, only those rows in the customers table that do not have at least one match with the orders table on customer_id will be returned.

There is no difference between the result sets for both statements.

Both statements will fail because Databricks SQL does not support those join types.

When the first statement is run, all rows from the customers table will be returned and only the customer_id from the orders table will be returned. When the second statement is run, only those rows in the customers table that do not have at least one match with the orders table on customer_id will be returned.

Based on the images you sent, the two statements are SQL queries for different types of joins between the customers and orders tables. A join is a way of combining the rows from two table references based on some criteria. The join type determines how the rows are matched and what kind of result set is returned. The first statement is a query for a LEFT SEMI JOIN, which returns only the rows from the left table reference (customers) that have a match with the right table reference (orders) on the join condition (customer_id). The second statement is a query for a LEFT ANTI JOIN, which returns only the rows from the left table reference (customers) that have no match with the right table reference (orders) on the join condition (customer_id). Therefore, the result sets for the two statements will differ in the following way:
The first statement will return a subset of the customers table that contains only the customers who have placed at least one order. The number of rows returned will be less than or equal to the number of rows in the customers table, depending on how many customers have orders. The number of columns returned will be the same as the number of columns in the customers table, as the LEFT SEMI JOIN does not include any columns from the orders table.
The second statement will return a subset of the customers table that contains only the customers who have not placed any order. The number of rows returned will be less than or equal to the number of rows in the customers table, depending on how many customers have no orders. The number of columns returned will be the same as the number of columns in the customers table, as the LEFT ANTI JOIN does not include any columns from the orders table.
The other options are not correct because:
A) The first statement will not return all data from the customers table, as it will exclude the customers who have no orders. The second statement will not return all data from the orders table, as it will exclude the orders that have a matching customer. Neither statement will fill in any missing data with NULL, as they do not return any columns from the other table.
C) There is a difference between the result sets for both statements, as explained above. The LEFT SEMI JOIN and the LEFT ANTI JOIN are not equivalent operations and will produce different outputs.
D) Both statements will not fail, as Databricks SQL does support those join types. Databricks SQL supports various join types, including INNER, LEFT OUTER, RIGHT OUTER, FULL OUTER, LEFT SEMI, LEFT ANTI, and CROSS. You can also use NATURAL, USING, or LATERAL keywords to specify different join criteria.
E) The first statement will not return only the customer_id from the orders table, as it will return all columns from the customers table. The second statement is correct, but it is not the only difference between the result sets.

NEW QUESTION 33
A data analyst has been asked to use the below table sales_table to get the percentage rank of products within region by the sales:

The result of the query should look like this:

Which of the following queries will accomplish this task?
A)

B)

C)

Option A

Option B

Option C

Option D

NEW QUESTION 34
A data analyst creates a Databricks SQL Query where the result set has the following schema:
region STRING
number_of_customer INT
When the analyst clicks on the “Add visualization” button on the SQL Editor page, which of the following types of visualizations will be selected by default?

There is no default. The user must choose a visualization type.

Line Chart

IBar Chart

Violin Chart

Histogram

NEW QUESTION 35
A data analyst needs to share a Databricks SQL dashboard with stakeholders that are not permitted to have accounts in the Databricks deployment. The stakeholders need to be notified every time the dashboard is refreshed.
Which approach can the data analyst use to accomplish this task with minimal effort/

By granting the stakeholders’ email addresses permissions to the dashboard

By adding the stakeholders’ email addresses to the refresh schedule subscribers list

By granting the stakeholders’ email addresses to the SQL Warehouse (formerly known as endpoint) subscribers list

By downloading the dashboard as a PDF and emailing it to the stakeholders each time it is refreshed

NEW QUESTION 36
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?

NEW QUESTION 37
Which of the following layers of the medallion architecture is most commonly used by data analysts?

None of these layers are used by data analysts

Gold

All of these layers are used equally by data analysts

Silver

Bronze

NEW QUESTION 38
A data analyst has set up a SQL query to run every four hours on a SQL endpoint, but the SQL endpoint is taking too long to start up with each run.
Which of the following changes can the data analyst make to reduce the start-up time for the endpoint while managing costs?

Reduce the SQL endpoint cluster size

Increase the SQL endpoint cluster size

Turn off the Auto stop feature

Increase the minimum scaling value

Use a Serverless SQL endpoint

NEW QUESTION 39
Delta Lake stores table data as a series of data files, but it also stores a lot of other information.
Which of the following is stored alongside data files when using Delta Lake?

None of these

Table metadata, data summary visualizations, and owner account information

Table metadata

Data summary visualizations

Owner account information

NEW QUESTION 40
A data analyst runs the following command:
SELECT age, country
FROM my_table
WHERE age >= 75 AND country = ‘canada’;
Which of the following tables represents the output of the above command?

NEW QUESTION 41
A data analyst has been asked to provide a list of options on how to share a dashboard with a client. It is a security requirement that the client does not gain access to any other information, resources, or artifacts in the database.
Which of the following approaches cannot be used to share the dashboard and meet the security requirement?

Download the Dashboard as a PDF and share it with the client.

Set a refresh schedule for the dashboard and enter the client’s email address in the “Subscribers” box.

Take a screenshot of the dashboard and share it with the client.

Generate a Personal Access Token that is good for 1 day and share it with the client.

Download a PNG file of the visualizations in the dashboard and share them with the client.

NEW QUESTION 42
Delta Lake stores table data as a series of data files, but it also stores a lot of other information.
Which of the following is stored alongside data files when using Delta Lake?

None of these

Table metadata, data summary visualizations, and owner account information

Table metadata

Data summary visualizations

Owner account information

NEW QUESTION 43
A data analyst has been asked to produce a visualization that shows the flow of users through a website.
Which of the following is used for visualizing this type of flow?

Heatmap

IChoropleth

Word Cloud

Pivot Table

Sankey

NEW QUESTION 44
Which of the following statements about a refresh schedule is incorrect?

A query can be refreshed anywhere from 1 minute lo 2 weeks

Refresh schedules can be configured in the Query Editor.

A query being refreshed on a schedule does not use a SQL Warehouse (formerly known as SQL Endpoint).

A refresh schedule is not the same as an alert.

You must have workspace administrator privileges to configure a refresh schedule

NEW QUESTION 45
How can a data analyst determine if query results were pulled from the cache?

Go to the Query History tab and click on the text of the query. The slideout shows if the results came from the cache.

Go to the Alerts tab and check the Cache Status alert.

Go to the Queries tab and click on Cache Status. The status will be green if the results from the last run came from the cache.

Go to the SQL Warehouse (formerly SQL Endpoints) tab and click on Cache. The Cache file will show the contents of the cache.

Go to the Data tab and click Last Query. The details of the query will show if the results came from the cache.

NEW QUESTION 46
A data analyst created and is the owner of the managed table my_ table. They now want to change ownership of the table to a single other user using Data Explorer.
Which of the following approaches can the analyst use to complete the task?

Edit the Owner field in the table page by selecting the Admins group

Edit the Owner field in the table page by removing their own account

Edit the Owner field in the table page by selecting the new owner’s account

Edit the Owner field in the table page by removing all access

Edit the Owner field in the table page by selecting All Users

NEW QUESTION 47
A data analyst wants the following output:
customer_name number_of_orders
John Doe 388
Zhang San 234
Which statement will produce this output?

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

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

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

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

NEW QUESTION 48
A data analyst has been asked to configure an alert for a query that returns the income in the accounts_receivable table for a date range. The date range is configurable using a Date query parameter.
The Alert does not work.
Which of the following describes why the Alert does not work?

Alerts don’t work with queries that access tables.

Queries that return results based on dates cannot be used with Alerts.

The wrong query parameter is being used. Alerts only work with Date and Time query parameters.

Queries that use query parameters cannot be used with Alerts.

The wrong query parameter is being used. Alerts only work with drogdown list query parameters, not dates.

NEW QUESTION 49
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?

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;

NEW QUESTION 50
A data analyst is working with gold-layer tables to complete an ad-hoc project. A stakeholder has provided the analyst with an additional dataset that can be used to augment the gold-layer tables already in use.
Which of the following terms is used to describe this data augmentation?

Data testing

Ad-hoc improvements

Last-mile

Last-mile ETL

Data enhancement

NEW QUESTION 51
Which of the following approaches can be used to connect Databricks to Fivetran for data ingestion?

Use Workflows to establish a SQL warehouse (formerly known as a SQL endpoint) for Fivetran to interact with

Use Delta Live Tables to establish a cluster for Fivetran to interact with

Use Partner Connect’s automated workflow to establish a cluster for Fivetran to interact with

Use Partner Connect’s automated workflow to establish a SQL warehouse (formerly known as a SQL endpoint) for Fivetran to interact with

Use Workflows to establish a cluster for Fivetran to interact with

NEW QUESTION 52
In which circumstance will there be a substantial difference between the variable’s mean and median values?