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Databricks Certified Data Analyst Associate Exam Sample Questions (Q43-Q48):

NEW QUESTION # 43
Which of the following benefits of using Databricks SQL is provided by Data Explorer?

A. It can be used to run UPDATE queries to update any tables in a database.
B. It can be used to view metadata and data, as well as view/change permissions.
C. It can be used to produce dashboards that allow data exploration.
D. It can be used to connect to third party Bl cools.
E. It can be used to make visualizations that can be shared with stakeholders.

Answer: B

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 # 44
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?

A. Turn off the Auto stop feature
B. Reduce the SQL endpoint cluster size
C. Increase the minimum scaling value
D. Use a Serverless SQL endpoint
E. Increase the SQL endpoint cluster size

Answer: D

Explanation:
A Serverless SQL endpoint is a type of SQL endpoint that does not require a dedicated cluster to run queries. Instead, it uses a shared pool of resources that can scale up and down automatically based on the demand. This means that a Serverless SQL endpoint can start up much faster than a SQL endpoint that uses a cluster, and it can also save costs by only paying for the resources that are used. A Serverless SQL endpoint is suitable for ad-hoc queries and exploratory analysis, but it may not offer the same level of performance and isolation as a SQL endpoint that uses a cluster. Therefore, a data analyst should consider the trade-offs between speed, cost, and quality when choosing between a Serverless SQL endpoint and a SQL endpoint that uses a cluster. Reference: Databricks SQL endpoints, Serverless SQL endpoints, SQL endpoint clusters

NEW QUESTION # 45
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?

Answer: D

Explanation:
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.

NEW QUESTION # 46
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 alter the Query to return two separate sets of results.
C. They will need to decide on a single data visualization to add to the dashboard.
D. They will need to add two separate visualizations to the dashboard based on the same Query.
E. They will need to create two separate dashboards.

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 # 47
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 price FROM customer_summary
B. SELECT 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 double(price(customer_spend, customer_units)) AS customer_price FROM customer_summary
E. SELECT function(price(customer_spend, customer_units)) AS customer_price FROM customer_summary

Answer: B

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 # 48
......

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