SNOWFLAKESnowflake SnowPro Advanced — Architect
The SnowPro Advanced: Architect certification validates your ability to design and implement comprehensive, scalable, and secure solutions on the Snowflake AI Data Cloud. It is for experienced architects who own complex data platform decisions, from data modeling and governance to performance optimization and cost management. Earning it demonstrates advanced, role-based expertise that sets you apart in the data community.
300 practice questions · Updated 2026-07-30
4Domains
12Objectives
114Concepts
300Questions
ARA-C01 Curriculum
Every domain, objective, and concept the ARA-C01 exam measures.
- Account and Role Hierarchy Design
- Role-Based Access Control (RBAC) Principles
- Custom Roles vs. Built-in Roles
- Role Inheritance and Privilege Propagation
- Account-Level vs. Object-Level Privileges
- Multi-Account Architecture
- Cross-Account Role Sharing
- Least Privilege Principle
- Separation of Duties
- Role Naming and Organization Conventions
- Account and Role Lifecycle Management
- Authentication methods
- Federated authentication with SAML
- OAuth integration
- Key-pair authentication
- Multi-factor authentication (MFA)
- Access control model
- Role hierarchy and privilege inheritance
- Custom roles and privileges
- Secure views and secure UDFs
- Row-level security
- Dynamic data masking
- Network policies
- SCIM provisioning
- Session policies
- Password policies
- Encryption Key Management
- Tri-Secret Secure
- Customer-Managed Keys (CMK)
- Encryption Options and Levels
- Encryption for Internal Stages
- Encryption for External Stages
- Unloading and Loading Encrypted Data
- Data Protection with Masking and Row-Level Security
- Network Policies and Data Egress Protection
- Auditing and Monitoring Encryption
- Scaling compute resources
- Scaling storage and performance
- Multi-cluster warehouses
- Auto-suspend and auto-resume
- Scaling for data ingestion
- Scaling for data transformation
- Scaling for concurrent access
- Designing for elasticity
- Data model design principles
- Storage strategy selection
- Clustering keys and micro-partitions
- Data lifecycle management
- Data sharing and replication
- Performance optimization for storage
- Multi-account architecture patterns
- Account-to-account data sharing
- Cross-cloud replication and failover
- Cross-cloud data sharing
- Network architecture for multi-account
- Governance and security across accounts
- Cost management in multi-account setups
- Account and organization management
- Pipeline design patterns
- Data ingestion methods
- Transformation strategies
- Streaming ingestion
- Batch ingestion optimization
- Data pipeline orchestration
- Incremental and change data capture
- Error handling and data quality
- Performance and cost optimization
- Security and governance in pipelines
- Streams overview
- Task overview
- Stream types
- Task scheduling
- Stream-task integration
- Task DAGs
- Stream consumption
- Error handling and retries
- Monitoring and governance
- Semi-structured data types
- Loading semi-structured data
- Querying semi-structured data
- Unstructured data storage
- Unstructured data processing
- Data transformation for semi-structured data
- Performance optimization for semi-structured data
- Data governance for semi-structured and unstructured data
- Warehouse Sizing and Scaling
- Warehouse Configuration Settings
- Query Queuing and Concurrency
- Caching Mechanisms
- Clustering Keys and Micro-partitions
- Data Pruning and Partition Elimination
- Query Profiling and Analysis
- Join Optimization
- Aggregation and Group By Optimization
- Materialized Views and Search Optimization
- Result Set and Query Result Caching
- Resource Monitors and Workload Management
- Performance Monitoring and Alerts
- Clustering Key Selection
- Clustering Depth and Maintenance
- Clustering Metadata and Pruning
- Materialized View Creation
- Materialized View Maintenance and Cost
- Materialized View Limitations
- Query Rewriting with Materialized Views
- Choosing Between Clustering and Materialized Views
- Query Profiling
- Warehouse Sizing and Scaling
- Clustering Keys and Automatic Clustering
- Search Optimization Service
- Materialized Views and Result Caching
- Data Layout and File Sizing
- Concurrency and Resource Management
- Monitoring and Alerting
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Percentages reflect share of the current practice bank, not official exam weightings — no structured per-skill weight is published for ARA-C01, so none is invented.