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Snowflake DAA-C01 Exam Syllabus Topics:

Snowflake SnowPro Advanced: Data Analyst Certification Sample Questions:

Question 1

A scorecard tile on a Snowsight dashboard shows a comparison between the industry average employee age (which is 34) and a company's average employee age (which is 38). The scorecard tile looks like this:
Comparison with industry average

How should this tile be interpreted?

A. 38 is the comparison and 12% is the average age change in the last year.
B. 38 is the value and 12% is the standard deviation.
C. 38 is the comparison and 12% is the projected industry growth.
D. 38 is the value and 12% is the percent difference from the comparison.

Question 2

Why would a Data Analyst use a dimensional model rather than a single flat table to meet BI requirements for a virtual warehouse? (Select TWO).

A. Snowflake generally performs better with dimensional modelling.
B. Dimensional modelling will save on storage space since it is denormalized.
C. Dimensions and facts allow power users to run ad-hoc analyses.
D. Combining facts and dimensions in a single flat table limits the scalability and flexibility.
E. Dimensional modelling will improve query performance over a single table.

Question 3

Which Snowflake SQL would a Data Analyst use in a trained Cortex model named forecast_model to retrieve the components that contribute to the predictions?

A. forecast_model!EXPLAIN_FEATURE_IMPORTANCE()
B. forecast_model!SHOW_EVALUATION_METRICS()
C. forecast_model!FORECAST()
D. forecast_model!SHOW_TRAINING_LOGS()

Question 4

A Data Analyst wants to use pandas code they have previously written to process a column of text and return multiple rows of parsed output for each input value. The Analyst wants to be able to join these results with other tables in a single transaction. Which type of extensibility feature should the Analyst use?

A. Stored procedure
B. External function
C. Vectorized User-Defined Table Function (UDTF)
D. User-Defined Function (UDF)

Question 5

Why would an INFER_SCHEMA table function be used?

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

Solutions: