Practice Free Databricks Certified Data Analyst Associate Exam Online Questions

Question #1

Which of the following should data analysts consider when working with personally identifiable information (PII) data?

A . Organization-specific best practices for Pll data
B . Legal requirements for the area in which the data was collected
C . None of these considerations
D . Legal requirements for the area in which the analysis is being performed
E . All of these considerations

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Question #2

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

A . Use Workflows to establish a SQL warehouse (formerly known as a SQL endpoint) for Fivetran to interact with
B . Use Delta Live Tables to establish a cluster for Fivetran to interact with
C . Use Partner Connect’s automated workflow to establish a cluster for Fivetran to interact with
D . Use Partner Connect’s automated workflow to establish a SQL warehouse (formerly known as a SQL endpoint) for Fivetran to interact with
E . Use Workflows to establish a cluster for Fivetran to interact with

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Question #3

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 alter the Query to return two separate sets of results.
B . They will need to add two separate visualizations to the dashboard based on the same Query.
C . They will need to create two separate dashboards.
D . They will need to decide on a single data visualization to add to the dashboard.
E . They will need to copy the Query and create one data visualization per query.

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Question #4

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?

A)

A . Option A
B . Option B
C . Option C
D . Option D
E . Option E

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Question #5

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 . Line Chart
C . IBar Chart
D . Histogram
E . There is no default. The user must choose a visualization type.

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Question #6

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?

A . 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.
B . 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.
C . There is no difference between the result sets for both statements.
D . Both statements will fail because Databricks SQL does not support those join types.
E . 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.

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Correct Answer: B
B

Explanation:

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.

Reference: JOIN | Databricks on AWS, JOIN – Azure Databricks – Databricks SQL | Microsoft Learn, array_join function | Databricks on AWS, Hints | Databricks on AWS

Question #7

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?

A . Alerts don’t work with queries that access tables.
B . Queries that return results based on dates cannot be used with Alerts.
C . The wrong query parameter is being used. Alerts only work with Date and Time query parameters.
D . Queries that use query parameters cannot be used with Alerts.
E . The wrong query parameter is being used. Alerts only work with drogdown list query parameters, not dates.

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Question #8

Which of the following statements describes descriptive statistics?

A . A branch of statistics that uses summary statistics to quantitatively describe and summarize data.
B . A branch of statistics that uses a variety of data analysis techniques to infer properties of an underlying distribution of probability.
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.

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Question #9

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 removing their own account
B . Edit the Owner field in the table page by selecting All Users
C . Edit the Owner field in the table page by selecting the new owner’s account
D . Edit the Owner field in the table page by selecting the Admins group
E . Edit the Owner field in the table page by removing all access

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Question #10

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 . Download the Dashboard as a PDF 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 . Generate a Personal Access Token that is good for 1 day and share it with the client.
E . Download a PNG file of the visualizations in the dashboard and share them with the client.

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