COF-C03 Exam Dumps - SnowPro Core Certification 2026 Exam

The ACCESS_HISTORY view in Snowflake provides detailed information about queries executed in the account, including metadata such as the time of execution, the user, and the SQL text of the queries. This view is available in the Snowflake Enterprise edition and higher editions. The Standard edition does not include this feature.

Snowflake Documentation: Access History

Snowflake Editions: Snowflake Pricing

The correct answer is C. Stored procedures .

In Snowflake, the CALL command is used to execute a stored procedure. Stored procedures can contain procedural logic and can be written in supported languages such as JavaScript, SQL, Python, Java, or Scala, depending on the type of procedure.

Why C is correct:

Stored procedures are invoked using the CALL statement.

Example:

CALL my_procedure();

This runs the stored procedure named my_procedure.

Why the other options are incorrect:

A. System functions are usually invoked in SQL expressions using SELECT or within statements, not with CALL.

B. Tasks are resumed, suspended, or managed using task-related commands, and they run on schedules or task graphs. They are not directly run with CALL.

D. External functions are called like regular SQL functions inside SQL statements, not with the CALL statement.

Official Snowflake documentation reference:

Snowflake documentation describes the CALL command as the command used to execute a stored procedure.

To avoid timeouts during large data uploads with thePUT commandin Snowflake, it is recommended to:

Compress files before loading: Compressed files are smaller and upload faster, reducing the risk of timeouts.

Increase the PARALLEL option value: This option allows more simultaneous upload threads, improving upload speed and efficiency for large datasets.

Semi-structured file formats and table staging do not directly impact timeouts, while enabling overwrite does not prevent timeouts but rather controls overwriting of existing files.

In Snowflake, a role is an access control entity that can be created as part of a hierarchy within an account. Roles are used to grant and manage privileges in a structured and scalable manner.

Understanding Roles:

Roles are logical entities that group privileges together.

They are used to control access to securable objects like tables, views, warehouses, and more.

Role Hierarchy:

Roles can be organized into a hierarchy, allowing for the inheritance of privileges.

A role higher in the hierarchy (parent role) can grant its privileges to a lower role (child role), simplifying privilege management.

Creating Roles:

Roles can be created using the CREATE ROLE command.

You can define parent-child relationships by granting one role to another.

Example Usage:

CREATE ROLE role1;

CREATE ROLE role2;

GRANT ROLE role1 TO role2;

In this example,role2inherits the privileges ofrole1.

Benefits:

Simplifies privilege management: Hierarchies allow for efficient privilege assignment and inheritance.

Enhances security: Roles provide a clear structure for managing access control, ensuring that privileges are granted appropriately.

Snowflake Documentation: Access Control in Snowflake

Snowflake Documentation: Creating and Managing Roles

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.

The correct answer is B. SELECT * FROM table_A TABLESAMPLE (100); .

TABLESAMPLE (100) samples 100 percent of the table, so it returns all rows from table_A.

Why B is correct:

SELECT *

FROM table_A TABLESAMPLE (100);

This requests a 100 percent sample, which is effectively the full table.

Why the other options are incorrect:

A. TABLESAMPLE (0) returns 0 percent of the table, not all rows.

C. SAMPLE (10) returns approximately 10 percent of the rows, not all rows.

D. TABLESAMPLE BERNOULLI (10) samples each row with a 10 percent probability, not all rows.

Official Snowflake documentation reference:

Snowflake documentation explains that SAMPLE / TABLESAMPLE can specify a probability percentage. A value of 100 represents 100 percent of the table.

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.

The correct answer is C. To ensure the same sample is returned each time a query is run .

The REPEATABLE keyword is used with a seed value to make sampling deterministic. This means Snowflake can return the same sample when the query is rerun with the same seed and the underlying data has not changed.

Why C is correct:

SELECT *

FROM table_A

SAMPLE BERNOULLI (10) REPEATABLE (123);

This returns a repeatable sample based on the seed value 123.

Why the other options are incorrect:

A. Returning a fixed number of rows uses SAMPLE ( < n > ROWS), not REPEATABLE.

B. REPEATABLE does not remove duplicates.

D. Block sampling is controlled with BLOCK or SYSTEM, not REPEATABLE.

Official Snowflake documentation reference:

Snowflake documentation explains that REPEATABLE or SEED specifies a seed value to make sample results repeatable.