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Snowflake DAA-C01 Exam Syllabus Topics:

Snowflake SnowPro Advanced: Data Analyst Certification Sample Questions:

1. A Data Analyst creates a dashboard showing the total credit consumption for each virtual warehouse as follows:

Why is the query failing?

A) INFORMATION_SCHEMA should be used instead of ACCOUNT_USAGE.
B) The current database context must be changed to SNOWFLAKE.
C) The query must be executed by a user with the ACCOUNTADMIN role.
D) DB1 must be authorized to have SELECT access to ACCOUNT_USAGE.

2. What scheme is used by Snowflake to estimate the approximate similarity between two or more data sets?

A) APPROX_PERCENTILE
B) HyperLogLog
C) APPROX_TOP_K
D) MINHASH

3. Why would an INFER_SCHEMA table function be used?

A) To retrieve the column definitions from a previously-loaded database table
B) To detect the file metadata schema from staged data files that contain semi-structured data
C) To detect the file metadata schema from staged data files that contain unstructured data
D) To detect the metadata schema from a table cell that contains JSON data

4. Which query will provide this data without incurring additional storage costs?

A) CREATE TABLE DEV.PUBLIC.TRANS_HIST AS (SELECT * FROM PROD.PUBLIC.TRANS_HIST WHERE extract(year from (TRANS_DATE)) = 2019);
B) CREATE TABLE DEV.PUBLIC.TRANS_HIST CLONE PROD.PUBLIC.TRANS_HIST;
C) CREATE TABLE DEV.PUBLIC.TRANS_HIST LIKE PROD.PUBLIC.TRANS_HIST;
D) CREATE TABLE DEV.PUBLIC.TRANS_HIST AS (SELECT * FROM PROD.PUBLIC.
TRANS_HIST);

5. 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?

A) SELECT CITY, CORR(ACTIVE_DRIVERS, AVERAGE_WAITING_TIME) FROM RIDE_DATA GROUP BY CITY;
B) SELECT CITY, SUM(ACTIVE_DRIVERS), AVG(AVERAGE_WAITING_TIME) FROM
RIDE_DATA GROUP BY CITY;
C) SELECT CITY, VARIANCE(ACTIVE_DRIVERS, AVERAGE_WAITING_TIME) FROM
RIDE_DATA GROUP BY CITY;
D) SELECT CITY, SUM(ACTIVE_DRIVERS), VARIANCE(AVERAGE_WAITING_TIME) FROM RIDE_DATA GROUP BY CITY;

Solutions: