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Snowflake COF-C03 Exam Syllabus Topics:

Section	Weight	Objectives
Snowflake Architecture & Core Concepts	31%	- Snowsight Interface, Core Platform Features - Cloud Services Layer, Compute Layer, Storage Layer - Virtual Warehouses, Clustering, Caching - Databases, Schemas, Objects, Data Types
Account Management & Data Governance	20%	- Trust Center, Data Lineage, Compliance - Security: Network Policies, MFA, Encryption - Access Control: RBAC, DAC, Roles, Privileges - Governance: Resource Monitors, Data Masking, Row/Column Security
Data Loading, Unloading & Connectivity	18%	- Stages, File Formats, COPY INTO, Snowpipe - External Integrations, Connectors, SnowSQL - Unloading Data, Export Options - Bulk Load, Streaming, Dynamic Tables
Performance Optimization, Querying & Transformation	21%	- Query Processing, Profiling, Optimization - SQL Transformations, Semi-structured/Unstructured Data - Materialized Views, Streams, Tasks, Pipelines - Cortex AI, Notebooks, Apache Iceberg Tables
Data Collaboration & Protection	10%	- Data Protection, Retention, Time Travel, Fail-safe - Data Clean Rooms, Collaboration Features - Secure Data Sharing, Listings, Marketplace

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Snowflake SnowPro® Core Certification 2026 Exam (COF-C03) Sample Questions (Q1090-Q1095):

NEW QUESTION # 1090
Which functions are used to manipulate semi-structured data? (Select TWO)

A. WIDTH_BUCKET
B. OBJECT_INSERT
C. LISTAGG
D. ARRAY_APPEND
E. HASH_AGG

Answer: B,D

Explanation:
Functions like ARRAY_APPEND() and OBJECT_INSERT() are system-defined for manipulating ARRAY and OBJECT types within VARIANT data structures.
Reference:
Snowflake Docs: Functions for Semi-Structured Data

NEW QUESTION # 1091
How does clustering depth impact query performance?

A. High clustering depth indicates that too many users are scanning the same micro-partitions, slowing query performance.
B. High clustering depth indicates that queries are taking advantage of caching and are running efficiently.
C. Low clustering depth indicates that there are many overlapping micro-partitions and that query pruning is efficient.
D. Low clustering depth indicates that there are few overlapping micro-partitions and that query pruning is efficient.

Answer: D

Explanation:
Clustering depth measures the average number of overlapping micro-partitions for specified columns.
A smaller clustering depth means fewer micro-partitions overlap, indicating that related values are stored in a more ordered and localized manner. This enables Snowflake to prune more irrelevant micro- partitions when a query filters on those columns, reducing the amount of data scanned and generally improving performance. Therefore, option C correctly states that low clustering depth corresponds to relatively little overlap and efficient pruning. High clustering depth indicates greater overlap and can cause more micro-partitions to be scanned. Snowflake notes that clustering depth is a diagnostic measurement rather than an absolute performance guarantee. Actual query performance remains the final indicator of whether a table is sufficiently well clustered.

NEW QUESTION # 1092
Which table type is supported by Snowflake Open Catalog to provide centralized read and write access to a table?

A. Dynamic
B. Hybrid
C. Iceberg
D. Event

Answer: C

Explanation:
Snowflake Open Catalog is a managed catalog implementation for Apache Iceberg tables and is based on the open Iceberg REST protocol. It provides centralized and secure access to Iceberg table metadata so compatible query engines can discover and work with governed tables. For an internally managed catalog, supported engines can read and write the registered Iceberg tables, while the table data and metadata remain in external cloud storage. Hybrid tables are Snowflake row-based tables for low- latency transactional workloads. Dynamic tables maintain query results through automated refreshes, and event tables store telemetry data. None of those table types is the open table format managed by Open Catalog. Therefore, the supported table type is Iceberg, making option B correct.

NEW QUESTION # 1093
An engineer has a connection named dev_project in the Snowflake CLI config.toml file. The connection specifies a role other than SYSADMIN.
The engineer then runs:
snow sql -c dev_project
When the engineer executes:
SELECT CURRENT_ROLE();
the query returns SYSADMIN.
Why did Snowflake CLI use the SYSADMIN role?

A. SYSADMIN is the engineer's default role and cannot be overridden by the config.toml file.
B. The [connections.dev_project] connection in the config.toml file was missing a warehouse parameter, w hich caused Snowflake CLI to ignore the role parameter.
C. The config.toml file is used only when the connection and role are also supplied as command-line parameters.
D. A SNOWFLAKE_ROLE environment variable was set to SYSADMIN, and environment variables take precedence over values in the config.toml file.

Answer: D

Explanation:
Snowflake CLI can obtain connection parameters from multiple sources. When the same connection parameter is specified in more than one place, the higher-precedence source overrides the lower-precedence source.
An environment variable such as SNOWFLAKE_ROLE overrides the role configured for the connection in config.toml. Therefore, when SNOWFLAKE_ROLE=SYSADMIN is present, the CLI session uses SYSADMIN, even when the selected connection specifies another role.
A missing warehouse does not cause Snowflake CLI to ignore the configured role. A user's default role can also be overridden when another valid role is explicitly supplied through a higher-precedence configuration source.
References:
Snowflake Documentation - Configuring connections for Snowflake CLI: https://docs.snowflake.com/en
/developer-guide/snowflake-cli/connecting/configure-connections
Snowflake Documentation - Connecting to Snowflake with Snowflake CLI: https://docs.snowflake.com/en
/developer-guide/snowflake-cli/connecting/connect
==

NEW QUESTION # 1094
Which role must be used to create resource monitors?

A. ACCOUNTADMIN
B. ORGADMIN
C. SECURITYADMIN
D. SYSADMIN

Answer: A

Explanation:
In Snowflake, the ACCOUNTADMIN role is required to create resource monitors. Resource monitors are used to manage and monitor the consumption of compute resources. The ACCOUNTADMIN role has the necessary privileges to create, configure, and manage resource monitors across the account.
References:
Snowflake Documentation: Resource Monitors

NEW QUESTION # 1095
......

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