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DAA-C01 Dumps - SnowPro Advanced: Data Analyst Exam Practice Exam Questions

Snowflake DAA-C01 - SnowPro Advanced: Data Analyst Exam Braindumps

Snowflake DAA-C01 - SnowPro Advanced Certification Practice Exam

  • Certification Provider:Snowflake
  • Exam Code:DAA-C01
  • Exam Name:SnowPro Advanced: Data Analyst Exam
  • Certification Name:SnowPro Advanced Certification
  • Total Questions:65 Questions and Answers With Detailed Explanations
  • Updated on:Based on the current DAA-C01 exam blueprint. Updated on Feb 20, 2026
  • Product Format: PDF (Portable) & Test Engine (Interactive) .
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Snowflake DAA-C01 This Week Results

DAA-C01 Question and Answers

Question # 1

When building a Snowsight dashboard that will allow users to filter data within a worksheet, which Snowflake system filters should be used?

Options:

A.  

Include the :datebucket system filter in a WHERE clause, and include the :daterange system filter in a GROUP BY clause.

B.  

Include the :daterange system filter in a SELECT clause, and include the :datebucket system filter in a GROUP BY clause.

C.  

Include the :datebucket system filter in a WHERE clause, and include the :daterange system filter in a SELECT clause.

D.  

Include the :daterange system filter in a WHERE clause, and include the :datebucket system filter in a GROUP BY clause.

Discussion 0
Question # 2

Which aggregate functions can be used to provide values for a given bucket in Snowsight charts? (Select THREE).

Options:

A.  

Any Value

B.  

Average

C.  

Standard Deviation

D.  

Mode

E.  

HLL

F.  

Max

Discussion 0
Question # 3

A Data Analyst for a ride-sharing company needs to assess the relationship between the number of active drivers in a city, and the average waiting time for passengers. Which query will determine if an increase in the number of active drivers is associated with a decrease in the average waiting time?

Options:

A.  

SELECT CITY, SUM(ACTIVE_DRIVERS), VARIANCE(AVERAGE_WAITING_TIME) FROM RIDE_DATA GROUP BY CITY;

B.  

SELECT CITY, VARIANCE(ACTIVE_DRIVERS, AVERAGE_WAITING_TIME) FROM RIDE_DATA GROUP BY CITY;

C.  

SELECT CITY, SUM(ACTIVE_DRIVERS), AVG(AVERAGE_WAITING_TIME) FROM RIDE_DATA GROUP BY CITY;

D.  

SELECT CITY, CORR(ACTIVE_DRIVERS, AVERAGE_WAITING_TIME) FROM RIDE_DATA GROUP BY CITY;

Discussion 0

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