Snowflake Updated COF-C02 Exam Questions and Answers by angel

 Snowflake supports several methods for authenticating users, including federated authentication, key-pair authentication, and OAuth. Federated authentication allows users to authenticate using their organization’s identity provider. Key-pair authentication uses a public-private key pair for secure login, and OAuth is an open standard for access delegation commonly used for token-based authentication. References: Authentication policies | Snowflake Documentation, Authenticating to the server | Snowflake Documentation, External API authentication and secrets | Snowflake Documentation.

Snowflake’s architecture allows for flexibility in account hosting across different cloud vendors and regions. This means that within a single organization, different Snowflake accounts can be set up in various cloud environments, such as AWS, Azure, or GCP, and in different geographical regions. This allows organizations to leverage the global infrastructure of multiple cloud providers and optimize their data storage and computing needs based on regional requirements, data sovereignty laws, and other considerations.

https://docs.snowflake.com/en/user-guide/intro-regions.html

 Materialized Views in Snowflake are designed to store the result of a query and can be refreshed to maintain up-to-date data. However, they have certain limitations, one of which is that they cannot be defined using a JOIN clause. This means that a Materialized View can only be created based on a single source table and cannot combine data from multiple tables using JOIN operations.

References:

Snowflake Documentation on Materialized Views

SnowPro® Core Certification Study Guide

A clustering key in Snowflake is used to co-locate similar data within the same micro-partitions to improve query performance, especially for large tables where data is not naturally ordered or has become fragmented due to extensive DML operations. The appropriate use of a clustering key can lead to improved scan efficiency and better column compression, resulting in faster query execution times.

The indicators that it may be appropriate to use a clustering key for a table include:

D. Queries on the table are running slower than expected: This can happen when the data in the table is not well-clustered, leading to inefficient scans during query execution.

E. The clustering depth for the table is large: A large clustering depth indicates that the table’s data is spread across many micro-partitions, which can degrade query performance as more data needs to be scanned.

References:

Snowflake Documentation on Clustering Keys & Clustered Tables

Snowflake Documentation on SYSTEM$CLUSTERING_INFORMATION

Stack Overflow discussion on cluster key selection in Snowflake