- (Topic 6)
From what stage can a Snowflake user omit the FROM clause while loading data into a table?

Correct Answer:B
In Snowflake, when loading data into a table using the COPY INTO command, the FROM clause can be omitted if loading from the table's stage, also known as the table stage. The table stage is a default location associated with each table where files can be temporarily stored for loading operations. This simplifies the data loading process by allowing direct loading from files that have been uploaded to the table's stage without specifying the stage explicitly in the COPY INTO command.
References:
✑ Snowflake Documentation: Loading Data into Tables

- (Topic 2)
Which snowflake objects will incur both storage and cloud compute charges? (Select TWO)

Correct Answer:AD
In Snowflake, both materialized views and transient tables will incur storage charges because they store data. They will also incur compute charges when queries are run against them, as compute resources are used to process the queries. References:
[COF-C02] SnowPro Core Certification Exam Study Guide

- (Topic 1)
What transformations are supported in a CREATE PIPE ... AS COPY ... FROM (....) statement? (Select TWO.)

Correct Answer:AD
In a CREATE PIPE ... AS COPY ... FROM (....) statement, the supported transformations include filtering data using an optional WHERE clause and omitting columns. The WHERE clause allows for the specification of conditions to filter the data that is being loaded, ensuring only relevant data is inserted into the table. Omitting columns enables the exclusion of certain columns from the data load, which can be useful when the incoming data contains more columns than are needed for the target table.
References:
✑ [COF-C02] SnowPro Core Certification Exam Study Guide
✑ Simple Transformations During a Load1

- (Topic 1)
What Snowflake features allow virtual warehouses to handle high concurrency workloads? (Select TWO)

Correct Answer:BD
Snowflake??s architecture is designed to handle high concurrency workloads through several features, two of which are particularly effective:
✑ B. The use of warehouse auto scaling: This feature allows Snowflake to automatically adjust the compute resources allocated to a virtual warehouse in response to the workload. If there is an increase in concurrent queries, Snowflake can scale up the resources to maintain performance.
✑ D. Use of multi-clustered warehouses: Multi-clustered warehouses enable Snowflake to run multiple clusters of compute resources simultaneously. This allows for the distribution of queries across clusters, thereby reducing the load on any single cluster and improving the system??s ability to handle a high number of concurrent queries.
These features ensure that Snowflake can manage varying levels of demand without manual intervention, providing a seamless experience even during peak usage. References:
✑ Snowflake Documentation on Virtual Warehouses
✑ SnowPro® Core Certification Study Guide

- (Topic 6)
What is a non-configurable feature that provides historical data that Snowflake may recover during a 7-day period?

Correct Answer:A
Fail-safe is a non-configurable feature in Snowflake that provides an additional layer of data protection beyond Time Travel. Time Travel allows users to access historical data within a configurable period (up to 90 days), while Fail-safe provides an additional 7-day period during which Snowflake retains historical data to recover from significant data loss or corruption incidents. This period is not accessible by users but can be used by Snowflake support to assist in data recovery efforts.References:Snowflake Documentation on Fail-safe and Time Travel

- (Topic 1)
Which account usage views are used to evaluate the details of dynamic data masking? (Select TWO)

Correct Answer:BE
To evaluate the details of dynamic data masking,
the POLICY_REFERENCES and ACCESS_HISTORY views in the account_usage schema are used. The POLICY_REFERENCES view provides information about the objects to which a masking policy is applied, and the ACCESS_HISTORY view contains details about access to the masked data, which can be used to audit and verify the application of
dynamic data masking policies.
References:
✑ [COF-C02] SnowPro Core Certification Exam Study Guide
✑ Snowflake Documentation on Dynamic Data Masking1