Question 1

What role does leveraging native data types play in Snowflake while working with different datasets?

Options :

A : Reduces query flexibility and optimization possibilities

B : Limits data type conversion capabilities

C : Impedes data compatibility with other platforms

D :

Improves query performance and storage efficiency

Answer: D

Question 2

In Snowflake, how does leveraging Parquet format contribute to optimizing query performance and storage efficiency?

Options :

A : Impedes data compression and decompression capabilities

B : Limits query execution time

C : Parquet format accelerates only metadata retrieval

D :

Enhances query performance and reduces storage requirements

Answer: D

Question 3

When maintaining reports and dashboards, why is it essential to build automated and repeatable tasks?

Options :

A : They ensure inconsistency in reports and dashboards.

B : Automated tasks increase the complexity of dashboard management.

C : Automated tasks reduce manual efforts, ensuring consistency.

D : Repeatable tasks hinder data updates in dashboards.

Answer: C

Question 4

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 5

What actions are involved in data discovery to identify necessary elements from available datasets in Snowflake? (Select all that apply)

Options :

A : Running SQL queries on tables

B : Performing data mining techniques

C : Evaluating necessary transformations

D :

Identifying missing data fields

Answer: A,C