Snowflake Updated COF-C02 Exam Questions and Answers by malakai

A federated authentication environment integrates Snowflake with an external identity provider (IdP) that supports SAML 2.0.

This setup ensures data security and privacy by leveraging centralized user identity management and avoiding storing user credentials in Snowflake.

Key advantages of a federated environment:

Centralized authentication simplifies user management.

Multi-Factor Authentication (MFA) support through IdPs enhances security.

Credentials remain external to Snowflake, minimizing risk exposure.

References:

Snowflake Documentation: Federated Authentication & SSO

Snowflake Security Best Practices

In Snowflake, horizontal scaling refers to adding more compute clusters to a virtual warehouse to handle higher query concurrency.

MAX_CLUSTER_COUNT determines the maximum number of clusters that can run simultaneously for a multi-cluster warehouse.

Increasing this value allows Snowflake to dynamically scale the number of clusters based on query demand.

Why Other Options Are Incorrect:

A. WAREHOUSE_SIZE: Increasing warehouse size changes the compute capacity of a single cluster (vertical scaling), not horizontal scaling.

C. MAX_CONCURRENCY_LEVEL: This controls query queuing and is unrelated to scaling the number of clusters.

D. MIN_CLUSTER_COUNT: This sets the minimum number of clusters but does not affect maximum horizontal scaling.

References:

Multi-Cluster Warehouses

Virtual Warehouse Scaling

A. Storage Costs: Different Snowflake editions have varying unit costs for storage. For example, Business Critical edition typically incurs higher costs compared to the Standard edition.

C. Compute Credits: The cost of compute credits also varies across editions, with higher editions offering more advanced features at a premium cost.

References:

Snowflake Documentation: Editions Overview

Snowflake Pricing Model

Snowflake streams are objects that enable users to track changes (inserts, updates, and deletes) to the data in tables, facilitating real-time data processing and integration workflows. Streams can be created on standard tables, capturing DML changes made to these tables so that downstream processes can consume the changes incrementally. This feature supports efficient data ETL, replication, and real-time analytics by providing a mechanism to process only the data that has changed. Note: The correct options should likely include a distinction between "Standard tables" and another object type such as "External tables" rather than repeating "Standard tables" twice.References: Snowflake Documentation on Streams