Free Practice Questions for Snowflake ARA-C01 Certification
Study with 386 exam-style practice questions designed to help you prepare for the Snowflake SnowPro Advanced: Architect (ARA-C01). All questions are aligned with the latest exam guide and include detailed explanations to help you master the material.
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Exam Details
Key information about Snowflake SnowPro Advanced: Architect (ARA-C01)
associate (intermediate)
Snowflake Continuing Education (CE) program (eligible ILT courses, equivalent/higher-level SnowPro Certification)
Active SnowPro Core Certified credential
2+ years of practical experience with Snowflake as an Architect in a production environment. Solution Architects, Database Architects, System Architects.
10 – 13 hours
2 years
Exam Topics & Skills Assessed
Skills measured (from the official study guide)
Domain 1: Account and Security
Subdomain 1.1: Design a Snowflake account and database strategy, based on business requirements.
Create and configure Snowflake parameters based on a central account and any additional accounts.
- Parameters (all levels) - Account parameters - Object parameters - Session parameters - Outline the Snowflake parameter hierarchy and the relationship between the parameter types.
List the benefits and limitations of one Snowflake account as compared to multiple Snowflake accounts.
- Isolate or segment accounts - Key considerations and constraints when defining an account strategy - Features/capabilities that can be leveraged across accounts - Identify use cases that are appropriate for account strategies
Subdomain 1.2: Design an architecture that meets data security, privacy, compliance, and governance requirements.
Configure Role-Based Access Control (RBAC) hierarchy
- Privilege inheritance - Database roles - System roles and associated best practices - Functional roles compared to access roles - Secondary roles
Data Access
- Storage integrations
Data Security
- Secure views - Data Governance - Column-level security - External tokenization - Dynamic Data Masking - Row-level security - Row access policies - Aggregate policies - Projection policies - Data lineage and dependencies - Object tagging - Compliance - Features of the different Snowflake editions - Payment Card Industry (PCI) Security Standard - Personal Identifiable Information (PII)/ Personal Health Information (PHI)
Subdomain 1.3: Outline Snowflake security principles and identify use cases where they should be applied.
Encryption
Network security
- Network policies - Network rules - External access - Access control privileges - Private connectivity - AWS PrivateLink - Azure Private Link - Google Cloud Private Service Connect
User, role, and grants provisioning
Authentication
- Authentication policies - Federated authentication - Single Sign-On (SSO) - OAuth - Multi-Factor Authentication (MFA) - Key-pair authentication - Security integration
Domain 2: Snowflake Architecture
Subdomain 2.1: Outline the benefits and limitations of various data models in a Snowflake environment.
Data models
- Data vault - Star schema
Use of key/column constraints (ENABLE/RELY/VALIDATE)
Subdomain 2.2: Design data sharing solutions, based on different use cases.
Use cases
- Sharing within the same organization/same Snowflake account - Sharing within a cloud region - Sharing across cloud regions - Sharing between different Snowflake accounts - Sharing to a non-Snowflake customer - Sharing across cloud providers - Sharing using Snowflake Data Clean Rooms
Snowflake Marketplace
Data Exchange
Data sharing methods
- Configure shares, account parameters, and privileges - Security patterns for data sharing - Outline the purpose, benefits, and capabilities of the multiple data sharing methods - Cross-Cloud Auto-Fulfillment
Subdomain 2.3: Create architecture solutions that support development lifecycles as well as workload requirements.
Data lake and environments
- Storage directory structure - Zones (data warehouse layers) - Support of DevOps/DataOps principles - Production/development/sandbox - Data workloads - Data warehouse - ELT/ETL
Development lifecycle support
- Migration - Deployment - CI/CD - Snowflake CLI - Git integration - Rollback process
Outline basic AI/ML pipelines and applications
- Snowpark Container Services - Snowflake ML functions - Cortex LLM functions - Streamlit - Snowflake Native App Framework
Subdomain 2.4: Given a scenario, outline how objects exist within the Snowflake object hierarchy and how the hierarchy impacts an architecture.
Roles
Virtual warehouses
Object hierarchy
- Databases - Schemas - Tables - Views - Stages - File formats - Functions - Procedures - Streams and tasks
Subdomain 2.5: Determine the appropriate data recovery solution in Snowflake and how data can be restored.
Backup/recovery
- Time Travel - Table types - Costs - Availability - Query performance impacts - Data corruption impacts - Zero-copy cloning - Fail-safe
Disaster recovery
- Replication and failover
Domain 3: Data Engineering
Subdomain 3.1: Determine the appropriate data loading or data unloading solution to meet business needs.
Data sources
- Data at rest - Data in motion - External sources and formats - Streaming data - Snowpipe - Change Data Capture (CDC) - OLTP/RDBMS sources - API sources
Data ingestion
- Bulk file upload - Snowpipe - Snowpipe Streaming - External tables - Reload process (load history) - Incremental updates compared to full updates - Iceberg tables (managed and unmanaged) - Parameters for copying data and addressing data handling errors
Architecture changes
- Schema detection and table schema evolution - Data source changes
Data unloading
Subdomain 3.2: Outline key tools in Snowflake’s ecosystem and how they interact with Snowflake.
Connectors
- Kafka - Spark - Python - Snowflake Connector for ServiceNow - Snowflake Connector for Google Analytics
Drivers
- JDBC - ODBC
API endpoints
- Use of system$allowlist - SQL API
SnowSQL
Snowflake CLI
Snowpark
- Python - Scala - Java
Subdomain 3.3: Determine the appropriate data transformation solution to meet business needs.
Views and tables
- Benefits, limitations, properties - Relationship and impact between the view and data types - Impact of costs - Dynamic tables
Staging layers and tables
Querying semi-structured data
- Flatten
Data processing
Stored procedures
Streams and tasks
Functions
- External functions - Performance impacts - User-Defined Functions (UDFs) - User-Defined Table Functions (UDTFs) - Secure functions
Domain 4: Performance Optimization
Subdomain 4.1: Outline performance tools, best practices, and appropriate scenarios where they should be applied.
Query profiling
- Interpret a Query Profile, identify bottlenecks, and outline recommendations - Metadata functions - Warehouse queuing - Warehouse spilling
Virtual warehouse configurations
- Auto-suspend/resume - Scale up/down (resizing) - Scale in/out (multi-cluster warehouse/auto-scaling) - Query acceleration service - Snowpark-optimized warehouses
Clustering
- Natural clustering - Auto-clustering - Clustering keys
Search optimization service
Caching
- Different cache layers - Cache expiration - Impact of costs
Subdomain 4.2: Troubleshoot performance issues with existing architectures.
Use of system clustering information
Warehouse monitoring
Optimization techniques
Micro-partition pruning
Monitoring and alerting
- ACCOUNT_USAGE and INFORMATION_SCHEMA views - Resource monitoring - Alerts and notifications (for example, errors, email) - Event tables (for example, logging, tracing)
Techniques & products