Databricks-Certified-Data-Analyst-Associate 試験問題を無料オンラインアクセス

A data analyst is working with the following table my_table:
customer_name dollars_spent
Hex Sprockets [125.34, 100.15, 9003.99]
Dented Fenders [16.99, 200.85, 33.49, 88.17]
The analyst wants to divide each value in the dollars_spent array by 100 to get the spend in terms of hundreds of dollars using the following code block:
SELECT
customer_name,
_______
FROM my_table;
Which line of code can be used to fill in the blank so that the above code block successfully completes the task?

• A.TRANSFORM(dollars_spent, value - > value / 100) AS hundreds_spent
• B.TRANSFORM(dollars_spent, dollars_spent / 100) AS hundreds_spent
• C.TRANSFORM(hundreds_spent, dollars_spent / 100)
• D.TRANSFORM(dollars_spent, value / 100) AS hundreds_spent

What describes Partner Connect in Databricks?

• A.it allows multi-directional connection between Databricks and Databricks partners easier.
• B.It exposes connection information to third-party tools via Databricks partners.
• C.it allows for free use of Databricks partner tools through a common API.
• D.It is a feature that runs Databricks partner tools on a Databricks SQL Warehouse (formerly known as a SQL endpoint).

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?

• A.A refresh schedule with an always-on SQL Warehouse (formerly known as SQL Endpoint
• B.A refresh schedule with stakeholders included as subscribers
• C.A refresh schedule with a Structured Streaming cluster
• D.A refresh schedule with an interval of 10 minutes or less

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?

• A.SELECT region, product, RANK() OVER ( PARTITION BY product ORDER BY sales DESC ) AS rankFROM sales_table;
• B.Option A
• C.Option C
• D.Option D
• E.SELECT region, product, RANK() OVER ( ORDER BY sales DESC ) AS rankFROM sales_table;
• F.SELECT region, product, RANK() OVER ( PARTITION BY region ORDER BY sales DESC ) AS rankFROM sales_table;
• G.SELECT region, product, RANK() OVER ( PARTITION BY region ) AS rankFROM sales_table;
• H.Option B

A data analyst has written and saved a series of queries that reveal trends that need to be monitored by several stakeholders.
Which tool should the data analyst use to share the results of all of the queries to be viewed at once?

• A.A Query History page
• B.A SQL warehouse
• C.A data visualization tab on a Query page
• D.A dashboard