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Snowflake COF-C03 Exam Syllabus

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Before starting your COF-C03 exam preparation, it is recommended to review the complete Snowflake SnowPro Core Certification 2026 Exam syllabus and carefully go through the exam objectives listed below. Once you understand the exam structure and objectives, you should practice using our free COF-C03 questions. We also provide premium COF-C03 practice test, fully updated according to the latest exam objectives, to help you accurately assess your preparedness for the actual exam.

Snowflake
Vendor
COF-C03
Exam Code
1126
Total Questions
5
Total Exam Domains

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COF-C03 EXAM QUESTIONS

Snowflake COF-C03 Exam Objectives

Section 1: Snowflake AI Data Cloud Features and Architecture
Weight:
31%
1.1 Describe and use the Snowflake architecture
  • Cloud Services layer
  • Compute layer 
  • Database Storage layer 
  • Compare and contrast the different Snowflake editions 
1.2 Use Snowflake Interfaces and tools
  • Snowsight
  • Snowflake CLI
  • IDE integrations (e.g., Visual Studio Code)
1.3 Differentiate Snowflake object hierarchy and types

Organization and account objects 
Database objects
  • Stages 
  • Schemas
  • Tables
  • Views
  • User-Defined Functions (UDFs)
  • File formats
  • Stored procedures
  • Pipes
  • Shares
  • Sequences
  • ML models
  • Applications
Session and context variables
  • Parameter hierarchy
  • Parameter precedence 
1.4 Configure virtual warehouses
Types 
  • Snowpark Optimized
  • Standard (Gen 1 and Gen 2)
  • Default warehouse for Notebooks* (Feature will not be tested until it’s globally GA)
Scaling policies
Warehouse type and configurations based on use cases
  • Ad-hoc queries
  • Data loading
  • BI and reporting
Best practices
  • Sizing (up, down)
  • Scaling (in, out)
  • Auto-Suspend
  • Workloads
Different teams
High concurrency
Complex queries 

1.5 Explain Snowflake storage concepts

Micro-partitions 
Data clustering
Table types
  • Permanent
  • Temporary
  • Transient
  • Apache Iceberg TM
  • External 
  • Dynamic 
Views types 
  • Standard 
  • Materialized 
  • Secure
1.6 Explain AI/ML and application development features

Snowflake Notebooks
Streamlit in Snowflake
Snowpark 
Snowflake Cortex 
  • AI SQL functions
  • Cortex Search
  • Cortex Analyst
Snowflake ML
Section 2: Account Management and Data Governance
Weight:
20%
2.1 Explain Snowflake security model and principles

Role-Based Access Control (RBAC)
Securable object hierarchy 
Discretionary access control (DAC) 
Network Policies 
Authentication
  • Multi-Factor Authentication (MFA) 
  • Federated Authentication
  • Single Sign-on (SSO)
  • OAuth 
  • Key-pair authentication
System-defined roles
Functional roles
  • Account roles 
  • Database roles
  • Custom roles
Secondary roles
Account identifiers 
Logging and tracing

2.2 Define data governance features and how they are used

Data masking
  • Row-level security
  • Column-level security
  • Object tagging
  • Privacy policies
  • Trust Center 
  • Encryption key management
  • Alerts
  • Notifications
  • Data replication and failover
  • Data lineage
2.3 Explain monitoring and cost management

Resource Monitors
  • Cost and warehouse monitoring
Calculating virtual warehouse credit usage
  • ACCOUNT_USAGE schema
Section 3: Data Loading, Unloading, and Connectivity
Weight:
18%
3.1 Perform data loading and unloading

File formats
Create and use stages
  • Internal stages
  • External stages 
  • Server-side encryption
  • Directory tables 
COPY INTO command
Error handling options 

3.2 Perform automated data ingestion
  • Snowpipe 
  • Snowpipe streaming
  • Streams 
  • Tasks
  • Dynamic tables
  • Openflow (Feature will not be tested until it’s globally GA)
3.3 Identify the different Snowflake Connectors and integrations
  • Snowflake drivers
  • Snowflake connectors
  • Storage integration
  • API integration 
  • Git integration
Section 4: Performance Optimization, Querying, and Transformation
Weight:
21%
4.1 Evaluate query performance

Query Performance Tuning
Query Profile/Query insights
  • Bytes spilled to storage 
  • Inefficient pruning
  • Exploding joins
  • Queuing
SNOWFLAKE.ACCOUNT_USAGE views (Snowflake database views)
  • Query attribution 
  • Query history
Workload management best practices
  • Grouping similar workloads
4.2 Optimize query performance 
  • Query acceleration service
  • Search optimization service
  • Clustering keys
  • Materialized views
4.3 Use Snowflake caching
  • Query result cache
  • Metadata cache 
  • Warehouse cache
4.4 Perform data transformation techniques

Using data
  • Structured
  • Semi-structured 
  • Unstructured
Aggregate functions
Applying SQL for query optimization
Window functions 
 
Section 5: Data Collaboration
Weight:
10%
5.1 Explain data collaboration and protection
  • Data replication and failover
  • Secure data sharing features
  • Cloning
  • Time Travel 
  • Fail-safe
5.2 Explain Snowflake's data sharing capabilities

Accounts 
  • Provider 
  • Consumer
  • Reader accounts
  • Secure Data Sharing
  • Sharing and resharing
  • Direct shares
  • Data clean rooms
5.3 Share data using the Snowflake Marketplace and listings 

Snowflake Marketplace
Listings
  • Private
  • Public
Native Apps
Info
https://learn.snowflake.com/en/certifications/snowpro-core-c03/