Free Sep-2026 Databricks-Certified-Data-Analyst-Associate Dumps are Available for Instant Access [Q38-Q60]

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Free Sep-2026 Databricks-Certified-Data-Analyst-Associate Dumps are Available for Instant Access

View All Databricks-Certified-Data-Analyst-Associate Actual Exam Questions Answers and Explanations for Free

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

Topic Details
Topic 1
  • 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 2
  • 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 3
  • 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 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.

 

QUESTION 38
Which of the following is a benefit of Databricks SQL using ANSI SQL as its standard SQL dialect?

 
 
 
 
 

QUESTION 39
A data analyst wants the following output:
customer_name number_of_orders
John Doe 388
Zhang San 234
Which statement will produce this output?

 
 
 
 

QUESTION 40
Which location can be used to determine the owner of a managed table?

 
 
 
 

QUESTION 41
Which of the following statements describes descriptive statistics?

 
 
 
 
 

QUESTION 42
Which statement describes descriptive statistics?

 
 
 
 

QUESTION 43
In which circumstance will there be a substantial difference between the variable’s mean and median values?

 
 
 
 

QUESTION 44
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)

D)

 
 
 
 

QUESTION 45
A data analyst runs the following command:
INSERT INTO stakeholders.suppliers TABLE stakeholders.new_suppliers;
What is the result of running this command?

 
 
 
 
 

QUESTION 46
A data analyst has recently joined a new team that uses Databricks SQL, but the analyst has never used Databricks before. The analyst wants to know where in Databricks SQL they can write and execute SQL queries.
On which of the following pages can the analyst write and execute SQL queries?

 
 
 
 
 

QUESTION 47
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?

 
 
 
 

QUESTION 48
Which of the following layers of the medallion architecture is most commonly used by data analysts?

 
 
 
 
 

QUESTION 49
The stakeholders.customers table has 15 columns and 3,000 rows of dat
a. The following command is run:

After running SELECT * FROM stakeholders.eur_customers, 15 rows are returned. After the command executes completely, the user logs out of Databricks.
After logging back in two days later, what is the status of the stakeholders.eur_customers view?

 
 
 
 
 

QUESTION 50
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?

 
 
 
 
 
 
 
 

QUESTION 51
Which statement describes descriptive statistics?

 
 
 
 

QUESTION 52
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?

 
 
 
 
 

QUESTION 53
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?

 
 
 
 

QUESTION 54
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?

 
 
 
 
 

QUESTION 55
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?

 
 
 
 
 

QUESTION 56
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?

 
 
 
 
 

QUESTION 57
A data engineering team has created a Structured Streaming pipeline that processes data in micro-batches and populates gold-level tables. The microbatches are triggered every minute.
A data analyst has created a dashboard based on this gold-level data. The project stakeholders want to see the results in the dashboard updated within one minute or less of new data becoming available within the gold- level tables.
Which of the following cautions should the data analyst share prior to setting up the dashboard to complete this task?

 
 
 
 
 

QUESTION 58
A table named user_ltv is being used to create a view that will be used by data analysts on various teams.
Users in the workspace are configured into groups, which are used for setting up data access using ACLs.
The user_ltv table has the following schema:
email STRING, age INT, ltv INT
The following view definition is executed:
CREATE VIEW user_ltv_no_minors AS
SELECT email, age, ltv
FROM user_ltv
WHERE
CASE
WHEN is_member( ” auditing ” ) THEN TRUE
ELSE age > = 18
END;
An analyst who is not a member of the auditing group executes the following query:
SELECT * FROM user_ltv_no_minors;
Which statement describes the results returned by this query?

 
 
 
 
 

QUESTION 59
A data analyst wants the following output:

Which statement will produce this output?

 
 
 
 

QUESTION 60
A data engineering team has created a Structured Streaming pipeline that processes data in micro-batches and populates gold-level tables. The microbatches are triggered every 10 minutes.
A data analyst has created a dashboard based on this gold level data. The project stakeholders want to see the results in the dashboard updated within 10 minutes or less of new data becoming available within the gold- level tables.
What is the ability to ensure the streamed data is included in the dashboard at the standard requested by the project stakeholders?

 
 
 
 

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