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  1. Home
  2. Snowflake Certification
  3. COF-C02 Exam
  4. Snowflake.COF-C02.v2026-01-13.q618 Dumps
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Question 401

Which transformation techniques are supported for bulk loading data into Snowflake using the copy into
<table> command? (Select TWO)

Correct Answer: B,E
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Question 402

While running a query on a virtual warehouse in auto-scale mode, additional clusters are stated immediately if which setting is configured?

Correct Answer: A
In Snowflake, auto-scaling allows virtual warehouses to automatically start additional clusters to handle increasing query loads. The setting that triggers the immediate start of additional clusters when a warehouse is running in auto-scale mode is:A. MAX_CLUSTER_COUNT is increased and new_max_clusters is greater than running_clusters: When the maximum number of clusters (MAX_CLUSTER_COUNT) is increased and the new maximum is higher than the number of clusters currently running (running_clusters), additional clusters will start immediately if required by the workload. This configuration ensures that performance scales with demand by allowing more compute resources to be provisioned as needed.
This behavior is designed to maintain performance by dynamically adjusting the compute resources without manual intervention, ensuring that queries are executed with minimal delay, even under varying workloads. It aligns with the principles of elasticity and scalability in cloud computing, particularly within Snowflake's architecture.
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Question 403

Which function can be used to convert semi-structured data into rows and columns?

Correct Answer: B
To convert semi-structured data into rows and columns in Snowflake, theFLATTENfunction is utilized.
* FLATTEN Function: This function takes semi-structured data (e.g., JSON) and transforms it into a relational table format by breaking down nested structures into individual rows. This process is essential for querying and analyzing semi-structured data using standard SQL operations.
Example Usage:
SELECT
f.value:attribute1 AS attribute1,
f.value:attribute2 AS attribute2
FROM
my_table,
LATERAL FLATTEN(input => my_table.semi_structured_column) f;
References:
* Snowflake Documentation on FLATTEN
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Question 404

A company strongly encourages all Snowflake users to self-enroll in Snowflake's default Multi-Factor Authentication (MFA) service to provide increased login security for users connecting to Snowflake.
Which application will the Snowflake users need to install on their devices in order to connect with MFA?

Correct Answer: B
https://docs.snowflake.com/en/user-guide/security-mfa.html
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Question 405

Which chart type is supported in Snowsight for Snowflake users to visualize data with dashboards?

Correct Answer: A
Snowsight, Snowflake's user interface for exploring, analyzing, and visualizing data, supports a variety of chart types for creating dashboards and visualizations. One of the supported chart types in Snowsight is the Area Chart (A). Area charts are useful for representing quantities over time and can be used to highlight volume change and rate of change, as well as to compare multiple quantities.
While Snowsight supports many types of visualizations to help users analyze their data effectively, including line charts, bar charts, and scatter plots, it's important to select the specific reference documentation or release notes for the most current list of supported chart types, as Snowflake continues to enhance and update Snowsight's capabilities.
As of the last update, Box plots (B), Heat grids (C), and Pie charts (D) are types of visualizations that may be supported in various analytics and visualization tools, but for the specific context of Snowsight's currently confirmed features, Area charts are a verified option for users to visualize their data.
Reference: Snowflake Documentation on Snowsight
(https://docs.snowflake.com/en/user-guide/ui-snowsight.html)
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