Databricks-Certified-Data-Analyst-Associate 무료 덤프문제 온라인 액세스

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

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

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.Copy the Query and create one data visualization per query.
• B.Alter the Query to return two separate sets of results.
• C.Decide on a single data visualization to add to the dashboard.
• D.Add two separate visualizations to the dashboard based on the same Query.

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

• A.The command fails because it is written incorrectly.
• B.The suppliers table now contains both the data it had before the command was run and the data from the new suppliers table, and any duplicate data is deleted.
• C.The suppliers table now contains both the data it had before the command was run and the data from the new suppliers table, including any duplicate data.
• D.The suppliers table now contains the data from the new suppliers table, and the new suppliers table now contains the data from the suppliers table.
• E.The suppliers table now contains only the data from the new suppliers table.

In which of the following situations should a data analyst use higher-order functions?

• A.When custom logic needs to be applied to simple, unnested data
• B.When built-in functions are taking too long to perform tasks
• C.When built-in functions need to run through the Catalyst Optimizer
• D.When custom logic needs to be converted to Python-native code
• E.When custom logic needs to be applied at scale to array data objects

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 FROM customer_summary
• D.SELECT PRICE customer_spend, customer_units AS customer_price FROM customer_summary
• E.SELECT price(customer_spend, customer_units) AS customer_price FROM customer_summary