Question 1

When performing forecasting using statistics and built-in functions, what role do these functions play?

Options :

A : These functions only apply to limited data types for forecasting.

B : They solely aid in data visualization without impacting the forecasting process.

C : They enable the creation of custom forecasting models as needed.

D :

They restrict forecasting to predefined models without flexibility.

Answer: C

Question 2

Why are materialized views valuable in data analysis compared to regular views?

Options :

A : Regular views simplify complex data structures for ease of analysis.

B :

They offer real-time updates reflecting instantaneous database changes.

C : Materialized views provide precomputed snapshots, improving query performance.

D : Materialized views restrict data access, enhancing security.

Answer: C

Question 3

What types of Snowflake functions are available for data analysis and manipulation? (Select all that apply)

Options :

A : Scalar functions

B : Complex functions

C : System functions

D : Aggregate functions

Answer: A,C,D

Question 4

When performing forecasting, which statistical method is commonly used based on historical data?

Options :

A :

Inferential statistics

B : Data normalization

C : Regression analysis

D : Simple data aggregation

Answer: C

Question 5

How do aggregate functions differ from window functions in Snowflake?

Options :

A : Window functions modify table structures.

B : Aggregate functions return single values.

C : Window functions work on entire tables.

D : Aggregate functions operate on groups of rows.

Answer: B,D