Snowflake COF-C02 Practice Exams
Last updated on Oct 22,2026- Exam Code: COF-C02
- Exam Name: SnowPro Core Certification Exam
- Certification Provider: Snowflake
- Latest update: Oct 22,2026
Question #101
Which Snowflake URL type is used by directory tables?
- A . File
- B . Pre-signed
- C . Scoped
- D . Virtual-hosted style
Correct Answer: C
C
Explanation:
The Snowflake URL type used by directory tables is the scoped URL. This type of URL provides access to files in a stage with metadata, such as the Snowflake file URL, for each file
C
Explanation:
The Snowflake URL type used by directory tables is the scoped URL. This type of URL provides access to files in a stage with metadata, such as the Snowflake file URL, for each file
Question #102
Which security models are used in Snowflake to manage access control? (Select TWO).
- A . Discretionary Access Control (DAC)
- B . Identity Access Management (1AM)
- C . Mandatory Access Control (MAC)
- D . Role-Based Access Control (RBAC)
- E . Security Assertion Markup Language (SAML)
Correct Answer: A, D
A, D
Explanation:
Snowflake uses both Discretionary Access Control (DAC) and Role-Based Access Control (RBAC) to manage access control. DAC allows object owners to grant access privileges to other users. RBAC assigns permissions to roles, and roles are then granted to users, making it easier to manage permissions based on user roles within the organization.
References: Snowflake Documentation: Access Control in Snowflake
A, D
Explanation:
Snowflake uses both Discretionary Access Control (DAC) and Role-Based Access Control (RBAC) to manage access control. DAC allows object owners to grant access privileges to other users. RBAC assigns permissions to roles, and roles are then granted to users, making it easier to manage permissions based on user roles within the organization.
References: Snowflake Documentation: Access Control in Snowflake
Question #103
Which feature of Snowflake’s Continuous Data Protection (CDP) has associated costs?
- A . Fail-safe
- B . Network policies
- C . End-to-end encryption
- D . Multi-Factor Authentication (MFA)
Correct Answer: A
A
Explanation:
Snowflake’s Continuous Data Protection (CDP) features encompass several mechanisms designed to protect data and ensure its availability and recoverability. Among these features, the one that has associated costs is Fail-safe.
Fail-safe is an additional layer of protection that kicks in after the Time Travel period expires. While Time Travel allows users to access historical data within a defined retention period (which can vary from 1 to 90 days depending on the Snowflake edition), Fail-safe provides a further 7 days (for a total of 7 additional days beyond the Time Travel period) during which Snowflake retains the data. This period is primarily intended for Snowflake’s internal operations to recover data in the event of extreme scenarios, such as significant operational failures, and is not directly accessible by customers for data recovery purposes.
The associated costs with Fail-safe arise because Snowflake continues to store the data beyond the customer-specified Time Travel period, thereby incurring additional storage costs. It’s important to note that while users do not incur direct costs for enabling Fail-safe (as it is an automatic feature of Snowflake), the extended storage of data during this period contributes to overall storage costs.
References:
Snowflake Documentation on Continuous Data Protection: Continuous Data Protection (CDP)
Snowflake Documentation on Fail-safe: Understanding Fail-safe
A
Explanation:
Snowflake’s Continuous Data Protection (CDP) features encompass several mechanisms designed to protect data and ensure its availability and recoverability. Among these features, the one that has associated costs is Fail-safe.
Fail-safe is an additional layer of protection that kicks in after the Time Travel period expires. While Time Travel allows users to access historical data within a defined retention period (which can vary from 1 to 90 days depending on the Snowflake edition), Fail-safe provides a further 7 days (for a total of 7 additional days beyond the Time Travel period) during which Snowflake retains the data. This period is primarily intended for Snowflake’s internal operations to recover data in the event of extreme scenarios, such as significant operational failures, and is not directly accessible by customers for data recovery purposes.
The associated costs with Fail-safe arise because Snowflake continues to store the data beyond the customer-specified Time Travel period, thereby incurring additional storage costs. It’s important to note that while users do not incur direct costs for enabling Fail-safe (as it is an automatic feature of Snowflake), the extended storage of data during this period contributes to overall storage costs.
References:
Snowflake Documentation on Continuous Data Protection: Continuous Data Protection (CDP)
Snowflake Documentation on Fail-safe: Understanding Fail-safe
Question #104
How can the outer array structure of a semi-structured file be removed?
- A . Use the parameter strip_outer_array = true in a COPY INTO <table> command.
- B . Set the file format to eliminate any outer array structure before initiating the COPY INTO <table> command.
- C . Filter the outer array structure using a PUT command with the include_outer_array = false parameter.
- D . Use the FLATTEN command with the outer_array = false parameter.
Correct Answer: A
A
Explanation:
In Snowflake, the parameter strip_outer_array = true can be set in the COPY INTO <table> command to remove the outer array structure from a semi-structured file. This parameter is useful for JSON files or similar data formats where an array might wrap the data, allowing Snowflake to directly load
the inner elements as table rows.
A
Explanation:
In Snowflake, the parameter strip_outer_array = true can be set in the COPY INTO <table> command to remove the outer array structure from a semi-structured file. This parameter is useful for JSON files or similar data formats where an array might wrap the data, allowing Snowflake to directly load
the inner elements as table rows.
Question #105
What are the least privileges needed to view and modify resource monitors? (Select TWO).
- A . SELECT
- B . OWNERSHIP
- C . MONITOR
- D . MODIFY
- E . USAGE
Correct Answer: C, D
C, D
Explanation:
To view and modify resource monitors, the least privileges needed are MONITOR and MODIFY. These privileges allow a user to monitor credit usage and make changes to resource monitors3.
C, D
Explanation:
To view and modify resource monitors, the least privileges needed are MONITOR and MODIFY. These privileges allow a user to monitor credit usage and make changes to resource monitors3.
Question #106
What type of columns does Snowflake recommend to be used as clustering keys? (Select TWO).
- A . A VARIANT column
- B . A column with very low cardinality
- C . A column with very high cardinality
- D . A column that is most actively used in selective filters
- E . A column that is most actively used in join predicates
Correct Answer: C, D
C, D
Explanation:
Snowflake recommends using columns with very high cardinality and those that are most actively used in selective filters as clustering keys. High cardinality columns have a wide range of unique values, which helps in evenly distributing the data across micro-partitions. Columns used in selective filters help in pruning the number of micro-partitions to scan, thus improving query performance.
References: Based on general database optimization principles.
C, D
Explanation:
Snowflake recommends using columns with very high cardinality and those that are most actively used in selective filters as clustering keys. High cardinality columns have a wide range of unique values, which helps in evenly distributing the data across micro-partitions. Columns used in selective filters help in pruning the number of micro-partitions to scan, thus improving query performance.
References: Based on general database optimization principles.
Question #107
How can a Snowflake user validate data that is unloaded using the COPY INTO <location> command?
- A . Load the data into a CSV file.
- B . Load the data into a relational table.
- C . Use the VALlDATlON_MODE – SQL statement.
- D . Use the validation mode = return rows statement.
Correct Answer: C
C
Explanation:
To validate data unloaded using the COPY INTO <location> command, a Snowflake user can use the VALIDATION_MODE parameter within the SQL statement to test the files for errors without loading them3.
C
Explanation:
To validate data unloaded using the COPY INTO <location> command, a Snowflake user can use the VALIDATION_MODE parameter within the SQL statement to test the files for errors without loading them3.
Question #108
How would a user run a multi-cluster warehouse in maximized mode?
- A . Configure the maximum clusters setting to "Maximum."
- B . Turn on the additional clusters manually after starting the warehouse.
- C . Set the minimum Clusters and maximum Clusters settings to the same value.
- D . Set the minimum clusters and maximum clusters settings to different values.
Correct Answer: C
C
Explanation:
To run a multi-cluster warehouse in maximized mode, a user should set the minimum and maximum number of clusters to the same value. This ensures that all clusters are available when the warehouse is started, providing maximum resources for query execution.
References: Snowflake Documentation2.
C
Explanation:
To run a multi-cluster warehouse in maximized mode, a user should set the minimum and maximum number of clusters to the same value. This ensures that all clusters are available when the warehouse is started, providing maximum resources for query execution.
References: Snowflake Documentation2.
Question #109
Which semi-structured file formats are supported when unloading data from a table? (Select TWO).
- A . ORC
- B . XML
- C . Avro
- D . Parquet
- E . JSON
Correct Answer: D, E
D, E
Explanation:
Semi-structured JSON, Parquet
Snowflake supports unloading data in several semi-structured file formats, including Parquet and JSON. These formats allow for efficient storage and querying of semi-structured data, which can be loaded directly into Snowflake tables without requiring a predefined schema12.
https://docs.snowflake.com/en/user-guide/data-unload-prepare.html#:~:text=Supported%20File%20Formats,-The%20following%20file&text=Delimited%20(CSV%2C%20TSV%2C%20etc.)
D, E
Explanation:
Semi-structured JSON, Parquet
Snowflake supports unloading data in several semi-structured file formats, including Parquet and JSON. These formats allow for efficient storage and querying of semi-structured data, which can be loaded directly into Snowflake tables without requiring a predefined schema12.
https://docs.snowflake.com/en/user-guide/data-unload-prepare.html#:~:text=Supported%20File%20Formats,-The%20following%20file&text=Delimited%20(CSV%2C%20TSV%2C%20etc.)
Question #110
From what stage can a Snowflake user omit the FROM clause while loading data into a table?
- A . The user stage
- B . The table stage
- C . The internal named stage
- D . The external named stage
Correct Answer: B
B
Explanation:
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
B
Explanation:
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