[May 27, 2026] Databricks-Certified-Data-Analyst-Associate PDF Recently Updated Questions Dumps to Improve Exam Score
Databricks-Certified-Data-Analyst-Associate Dumps Full Questions with Free PDF Questions to Pass
Databricks Databricks-Certified-Data-Analyst-Associate Exam Syllabus Topics:
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NEW QUESTION # 37
Query History provides Databricks SQL users with a lot of benefits. A data analyst has been asked to share all of these benefits with their team as part of a training exercise. One of the benefit statements the analyst provided to their team is incorrect.
Which statement about Query History is incorrect?
- A. It can be used to view the query plan of queries that have run.
- B. It can be used to debug queries.
- C. It can be used to troubleshoot slow running queries.
- D. It can be used to automate query execution on multiple warehouses (formerly endpoints).
Answer: D
Explanation:
Query History in Databricks SQL is intended for reviewing executed queries, understanding their execution plans, and identifying performance issues or errors for debugging purposes. It allows users to analyze query duration, resources used, and potential bottlenecks. However, Query History does not provide any capability to automate the execution of queries across multiple warehouses; automation must be handled through jobs or external orchestration tools, not through the Query History feature itself.
NEW QUESTION # 38
A data analyst has created a Query in Databricks SQL, and now wants to create two data visualizations from that Query and add both of those data visualizations to the same Databricks SQL Dashboard.
Which step will the data analyst need to take when creating and adding both data visualizations to the Databricks SQL Dashboard?
- A. Decide on a single data visualization to add to the dashboard.
- B. Alter the Query to return two separate sets of results.
- C. Copy the Query and create one data visualization per query.
- D. Add two separate visualizations to the dashboard based on the same Query.
Answer: D
NEW 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?
- A. SELECT customerjiame, (order_id) number_of_orders
FROM customers
JOIN orders
ON customers.customer_id = orders.customer_id; - B. SELECT customerjiame, count(order_id)
FROM customers
JOIN orders
ON customers.customer_id = orders.customer_id GROUP BY customerjiame; - C. 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; - D. SELECT customer_name, count(order_id) number_of_orders
FROM customers
JOIN orders
ON customers.customer_id = orders.customer_id USE customer_name;
Answer: C
NEW QUESTION # 40
Which of the following statements describes descriptive statistics?
- A. A branch of statistics that uses a variety of data analysis techniques to infer properties of an underlying distribution of probability.
- B. A branch of statistics that uses summary statistics to quantitatively describe and summarize data.
- C. A branch of statistics that uses quantitative variables that must take on a finite or countably infinite set of values.
- D. A branch of statistics that uses summary statistics to categorically describe and summarize data.
- E. A branch of statistics that uses quantitative variables that must take on an uncountable set of values.
Answer: B
Explanation:
Descriptive statistics is a branch of statistics that uses summary statistics, such as mean, median, mode, standard deviation, range, frequency, or correlation, to quantitatively describe and summarize data. Descriptive statistics can help data analysts understand the main features of a data set, such as its central tendency, variability, or distribution. Descriptive statistics can also help data analysts visualize data using charts, graphs, or tables. Descriptive statistics do not make any inferences or predictions about the data, unlike inferential statistics, which use data analysis techniques to infer properties of an underlying population or probability distribution from a sample of data. Reference: Databricks - Descriptive Statistics, Databricks - Data Analysis with Databricks SQL
NEW QUESTION # 41
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?
- A. Violin Chart
- B. IBar Chart
- C. Histogram
- D. There is no default. The user must choose a visualization type.
- E. Line Chart
Answer: B
Explanation:
According to the Databricks SQL documentation, when a data analyst clicks on the "Add visualization" button on the SQL Editor page, the default visualization type is Bar Chart. This is because the result set has two columns: one of type STRING and one of type INT. The Bar Chart visualization automatically assigns the STRING column to the X-axis and the INT column to the Y-axis. The Bar Chart visualization is suitable for showing the distribution of a numeric variable across different categories. Reference: Visualization in Databricks SQL, Visualization types
NEW QUESTION # 42
A data analyst has created a Query in Databricks SQL, and now they want to create two data visualizations from that Query and add both of those data visualizations to the same Databricks SQL Dashboard.
Which of the following steps will they need to take when creating and adding both data visualizations to the Databricks SQL Dashboard?
- A. They will need to copy the Query and create one data visualization per query.
- B. They will need to create two separate dashboards.
- C. They will need to alter the Query to return two separate sets of results.
- D. They will need to add two separate visualizations to the dashboard based on the same Query.
- E. They will need to decide on a single data visualization to add to the dashboard.
Answer: D
Explanation:
A data analyst can create multiple visualizations from the same query in Databricks SQL by clicking the + button next to the Results tab and selecting Visualization. Each visualization can have a different type, name, and configuration. To add a visualization to a dashboard, the data analyst can click the vertical ellipsis button beneath the visualization, select + Add to Dashboard, and choose an existing or new dashboard. The data analyst can repeat this process for each visualization they want to add to the same dashboard. Reference: Visualization in Databricks SQL, Visualize queries and create a dashboard in Databricks SQL
NEW QUESTION # 43
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?
- A. Generate a Personal Access Token that is good for 1 day and share it with the client.
- B. Set a refresh schedule for the dashboard and enter the client's email address in the "Subscribers" box.
- C. Take a screenshot of the dashboard and share it with the client.
- D. Download the Dashboard as a PDF and share it with the client.
- E. Download a PNG file of the visualizations in the dashboard and share them with the client.
Answer: A
Explanation:
The approach that cannot be used to share the dashboard and meet the security requirement is D. Generating a Personal Access Token that is good for 1 day and sharing it with the client. This approach would give the client access to the Databricks workspace using the token owner's identity and permissions, which could expose other information, resources, or artifacts in the database1. The other approaches can be used to share the dashboard and meet the security requirement because:
A) Downloading the Dashboard as a PDF and sharing it with the client would only provide a static snapshot of the dashboard without any interactive features or access to the underlying data2.
B) Setting a refresh schedule for the dashboard and entering the client's email address in the "Subscribers" box would send the client an email with the latest dashboard results as an attachment or a link to a secure web page3. The client would not be able to access the Databricks workspace or the dashboard itself.
C) Taking a screenshot of the dashboard and sharing it with the client would also only provide a static snapshot of the dashboard without any interactive features or access to the underlying data4.
E) Downloading a PNG file of the visualizations in the dashboard and sharing them with the client would also only provide a static snapshot of the visualizations without any interactive features or access to the underlying data5. Reference:
1: Personal access tokens
2: Download as PDF
3: Automatically refresh a dashboard
4: Take a screenshot
5: Download a PNG file
NEW QUESTION # 44
In which of the following situations will the mean value and median value of variable be meaningfully different?
- A. When the variable contains a lot of extreme outliers
- B. When the variable contains no missing values
- C. When the variable is of the boolean type
- D. When the variable is of the categorical type
- E. When the variable contains no outliers
Answer: A
Explanation:
The mean value of a variable is the average of all the values in a data set, calculated by dividing the sum of the values by the number of values. The median value of a variable is the middle value of the ordered data set, or the average of the middle two values if the data set has an even number of values. The mean value is sensitive to outliers, which are values that are very different from the rest of the data. Outliers can skew the mean value and make it less representative of the central tendency of the data. The median value is more robust to outliers, as it only depends on the middle values of the data. Therefore, when the variable contains a lot of extreme outliers, the mean value and the median value will be meaningfully different, as the mean value will be pulled towards the outliers, while the median value will remain close to the majority of the data1. Reference: Difference Between Mean and Median in Statistics (With Example) - BYJU'S
NEW QUESTION # 45
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/
- A. By adding the stakeholders' email addresses to the refresh schedule subscribers list
- B. By downloading the dashboard as a PDF and emailing it to the stakeholders each time it is refreshed
- C. By granting the stakeholders' email addresses to the SQL Warehouse (formerly known as endpoint) subscribers list
- D. By granting the stakeholders' email addresses permissions to the dashboard
Answer: A
Explanation:
To share a Databricks SQL dashboard with stakeholders who do not have accounts in the Databricks deployment and ensure they are notified upon each refresh, the data analyst can add the stakeholders' email addresses to the dashboard's refresh schedule subscribers list. This approach allows the stakeholders to receive email notifications containing the latest dashboard updates without requiring them to have direct access to the Databricks workspace. This method is efficient and minimizes effort, as it automates the notification process and ensures stakeholders remain informed of the most recent data insights.
NEW QUESTION # 46
Which of the following should data analysts consider when working with personally identifiable information (PII) data?
- A. None of these considerations
- B. Organization-specific best practices for Pll data
- C. Legal requirements for the area in which the data was collected
- D. All of these considerations
- E. Legal requirements for the area in which the analysis is being performed
Answer: D
Explanation:
Data analysts should consider all of these factors when working with PII data, as they may affect the data security, privacy, compliance, and quality. PII data is any information that can be used to identify a specific individual, such as name, address, phone number, email, social security number, etc. PII data may be subject to different legal and ethical obligations depending on the context and location of the data collection and analysis. For example, some countries or regions may have stricter data protection laws than others, such as the General Data Protection Regulation (GDPR) in the European Union. Data analysts should also follow the organization-specific best practices for PII data, such as encryption, anonymization, masking, access control, auditing, etc. These best practices can help prevent data breaches, unauthorized access, misuse, or loss of PII data. Reference:
How to Use Databricks to Encrypt and Protect PII Data
Automating Sensitive Data (PII/PHI) Detection
Databricks Certified Data Analyst Associate
NEW QUESTION # 47
Which of the following benefits of using Databricks SQL is provided by Data Explorer?
- A. It can be used to connect to third party Bl cools.
- B. It can be used to produce dashboards that allow data exploration.
- C. It can be used to view metadata and data, as well as view/change permissions.
- D. It can be used to make visualizations that can be shared with stakeholders.
- E. It can be used to run UPDATE queries to update any tables in a database.
Answer: C
Explanation:
Data Explorer is a user interface that allows you to discover and manage data, schemas, tables, models, and permissions in Databricks SQL. You can use Data Explorer to view schema details, preview sample data, and see table and model details and properties. Administrators can view and change owners, and admins and data object owners can grant and revoke permissions1. Reference: Discover and manage data using Data Explorer
NEW QUESTION # 48
An analyst writes a query that contains a query parameter. They then add an area chart visualization to the query. While adding the area chart visualization to a dashboard, the analyst chooses "Dashboard Parameter" for the query parameter associated with the area chart.
Which of the following statements is true?
- A. The area chart will use whatever value is chosen on the dashboard at the time the area chart is added to the dashboard.
- B. The area chart will use whatever value is input by the analyst when the visualization is added to the dashboard. The parameter cannot be changed by the user afterwards.
- C. The area chart will use whatever is selected in the Dashboard Parameter along with all of the other visualizations in the dashboard that use the same parameter.
- D. The area chart will convert to a Dashboard Parameter.
- E. The area chart will use whatever is selected in the Dashboard Parameter while all or the other visualizations will remain changed regardless of their parameter use.
Answer: C
Explanation:
A Dashboard Parameter is a parameter that is configured for one or more visualizations within a dashboard and appears at the top of the dashboard. The parameter values specified for a Dashboard Parameter apply to all visualizations reusing that particular Dashboard Parameter1. Therefore, if the analyst chooses "Dashboard Parameter" for the query parameter associated with the area chart, the area chart will use whatever is selected in the Dashboard Parameter along with all of the other visualizations in the dashboard that use the same parameter. This allows the user to filter the data across multiple visualizations using a single parameter widget2. Reference: Databricks SQL dashboards, Query parameters
NEW QUESTION # 49
A data analyst has been asked to count the number of customers in each region and has written the following query:
If there is a mistake in the query, which of the following describes the mistake?
- A. The query is using count('). which will count all the customers in the customers table, no matter the region.
- B. The query is selecting region but region should only occur in the ORDER BY clause.
- C. The query is using ORDER BY. which is not allowed in an aggregation.
- D. There are no mistakes in the query.
- E. The query is missing a GROUP BY region clause.
Answer: E
Explanation:
In the provided SQL query, the data analyst is trying to count the number of customers in each region. However, they made a mistake by not including the "GROUP BY" clause to group the results by region. Without this clause, the query will not return counts for each distinct region but rather an error or incorrect result. Reference: The need for a GROUP BY clause in such queries can be understood from Databricks SQL documentation: Databricks SQL.
I also noticed that you uploaded an image with your question. The image shows a snippet of an SQL query written in plain text on a white background. The query is attempting to select regions and count customers from a "customers" table and order the results by region. There's no visible syntax highlighting or any other color - it's monochromatic. The query is the same as the one in your question. I'm not sure why you included the image, but maybe you wanted to show me the exact format of your query. If so, you can also use code blocks to display formatted content such as SQL queries. For example, you can write:
SELECT region, count(*) AS number_of_customers
FROM customers
ORDER BY region;
This way, you can avoid uploading images and make your questions more clear and concise. I hope this helps.
NEW QUESTION # 50
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?
- A.
- B.
- C.
- D.
Answer: C
NEW QUESTION # 51
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?
- A. Edit the Owner field in the table page by selecting the Admins group
- B. Edit the Owner field in the table page by removing all access
- C. Edit the Owner field in the table page by selecting All Users
- D. Edit the Owner field in the table page by selecting the new owner's account
- E. Edit the Owner field in the table page by removing their own account
Answer: D
Explanation:
The Owner field in the table page shows the current owner of the table and allows the owner to change it to another user or group. To change the ownership of the table, the owner can click on the Owner field and select the new owner from the drop-down list. This will transfer the ownership of the table to the selected user or group and remove the previous owner from the list of table access control entries1. The other options are incorrect because:
A . Removing the owner's account from the Owner field will not change the ownership of the table, but will make the table ownerless2.
B . Selecting All Users from the Owner field will not change the ownership of the table, but will grant all users access to the table3.
D . Selecting the Admins group from the Owner field will not change the ownership of the table, but will grant the Admins group access to the table3.
E . Removing all access from the Owner field will not change the ownership of the table, but will revoke all access to the table4. Reference:
1: Change table ownership
2: Ownerless tables
3: Table access control
4: Revoke access to a table
NEW QUESTION # 52
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 dat
a. 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?
- A. A refresh schedule with an interval of 10 minutes or less
- B. A refresh schedule with stakeholders included as subscribers
- C. A refresh schedule with an always-on SQL Warehouse (formerly known as SQL Endpoint
- D. A refresh schedule with a Structured Streaming cluster
Answer: A
Explanation:
In this scenario, the data engineering team has configured a Structured Streaming pipeline that updates the gold-level tables every 10 minutes. To ensure that the dashboard reflects the most recent data, it is essential to set the dashboard's refresh schedule to an interval of 10 minutes or less. This synchronization ensures that stakeholders view the latest information shortly after it becomes available in the gold-level tables. Options B, C, and D do not directly address the requirement of aligning the dashboard refresh frequency with the data update interval.
NEW QUESTION # 53
The stakeholders.customers table has 15 columns and 3,000 rows of data. 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?
- A. The view is not available in the metastore, but the underlying data can be accessed with SELECT * FROM delta. `stakeholders.eur_customers`.
- B. The view has been dropped.
- C. The view remains available and SELECT * FROM stakeholders.eur_customers will execute correctly.
- D. The view remains available but attempting to SELECT from it results in an empty result set because data in views are automatically deleted after logging out.
- E. The view has been converted into a table.
Answer: B
Explanation:
The command you sent creates a TEMP VIEW, which is a type of view that is only visible and accessible to the session that created it. When the session ends or the user logs out, the TEMP VIEW is automatically dropped and cannot be queried anymore. Therefore, after logging back in two days later, the status of the stakeholders.eur_customers view is that it has been dropped and SELECT * FROM stakeholders.eur_customers will result in an error. The other options are not correct because:
A) The view does not remain available, as it is a TEMP VIEW that is dropped when the session ends or the user logs out.
C) The view is not available in the metastore, as it is a TEMP VIEW that is not registered in the metastore. The underlying data cannot be accessed with SELECT * FROM delta. stakeholders.eur_customers, as this is not a valid syntax for querying a Delta Lake table. The correct syntax would be SELECT * FROM delta.dbfs:/stakeholders/eur_customers, where the location path is enclosed in backticks. However, this would also result in an error, as the TEMP VIEW does not write any data to the file system and the location path does not exist.
D) The view does not remain available, as it is a TEMP VIEW that is dropped when the session ends or the user logs out. Data in views are not automatically deleted after logging out, as views do not store any data. They are only logical representations of queries on base tables or other views.
E) The view has not been converted into a table, as there is no automatic conversion between views and tables in Databricks. To create a table from a view, you need to use a CREATE TABLE AS statement or a similar command. Reference: CREATE VIEW | Databricks on AWS, Solved: How do temp views actually work? - Databricks - 20136, temp tables in Databricks - Databricks - 44012, Temporary View in Databricks - BIG DATA PROGRAMMERS, Solved: What is the difference between a Temporary View an ...
NEW QUESTION # 54
A data analyst has created a user-defined function using the following line of code:
CREATE FUNCTION price(spend DOUBLE, units DOUBLE)
RETURNS DOUBLE
RETURN spend / units;
Which of the following code blocks can be used to apply this function to the customer_spend and customer_units columns of the table customer_summary to create column customer_price?
- A. SELECT double(price(customer_spend, customer_units)) AS customer_price FROM customer_summary
- B. SELECT function(price(customer_spend, customer_units)) AS customer_price FROM customer_summary
- C. SELECT price(customer_spend, customer_units) AS customer_price FROM customer_summary
- D. SELECT price FROM customer_summary
- E. SELECT PRICE customer_spend, customer_units AS customer_price FROM customer_summary
Answer: C
Explanation:
A user-defined function (UDF) is a function defined by a user, allowing custom logic to be reused in the user environment1. To apply a UDF to a table, the syntax is SELECT udf_name(column_name) AS alias FROM table_name2. Therefore, option E is the correct way to use the UDF price to create a new column customer_price based on the existing columns customer_spend and customer_units from the table customer_summary. Reference:
What are user-defined functions (UDFs)?
User-defined scalar functions - SQL
V
NEW QUESTION # 55
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?
- A. Edit the Owner field in the table page by selecting the Admins group
- B. Edit the Owner field in the table page by removing all access
- C. Edit the Owner field in the table page by selecting All Users
- D. Edit the Owner field in the table page by selecting the new owner's account
- E. Edit the Owner field in the table page by removing their own account
Answer: D
Explanation:
The Owner field in the table page shows the current owner of the table and allows the owner to change it to another user or group. To change the ownership of the table, the owner can click on the Owner field and select the new owner from the drop-down list. This will transfer the ownership of the table to the selected user or group and remove the previous owner from the list of table access control entries1. The other options are incorrect because:
A) Removing the owner's account from the Owner field will not change the ownership of the table, but will make the table ownerless2.
B) Selecting All Users from the Owner field will not change the ownership of the table, but will grant all users access to the table3.
D) Selecting the Admins group from the Owner field will not change the ownership of the table, but will grant the Admins group access to the table3.
E) Removing all access from the Owner field will not change the ownership of the table, but will revoke all access to the table4. Reference:
1: Change table ownership
2: Ownerless tables
3: Table access control
4: Revoke access to a table
NEW QUESTION # 56
......
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