SnowPro Advanced: Architect Certification Practice test will test the ability to:
● Design an end-to-end data flow from source to consumption using the Snowflake data platform.
● Design and deploy a data architecture that meets business, security, and compliance requirements.
● Select appropriate Snowflake and third-party tools to optimize architecture performance.
● Design and deploy a shared data set using the Snowflake Data Marketplace and Data Exchange
Exam Topics covered are:
1.0 Domain: Account and Security
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.
● List the benefits and limitations of one Snowflake account as compared to
multiple Snowflake accounts.
1.2 Design an architecture that meets data security, privacy, compliance, and
governance requirements.
● Configure Role Based Access Control (RBAC) hierarchy
● System roles and associated best practices
● Data Access
● Data Security
● Compliance
1.3 Outline Snowflake security principles and identify use cases where they should be
applied.
● Encryption
● Network security
● User, Role, Grants provisioning
● Authentication
2.0 Domain: Snowflake Architecture
2.1 Outline the benefits and limitations of various data models in a Snowflake
environment.
● Data Models
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 platforms
● Data Marketplace
● Data Exchange
● Data Sharing Methods
2.3 Create architecture solutions that support Development Lifecycles as well as
workload requirements.
● Data Lake and Environments
● Workloads
● Development Lifecycle Support
2.4 Given a scenario, outline how objects exist within the Snowflake Object hierarchy
and how the hierarchy impacts an architecture.
● Roles
● Warehouses
● Object hierarchy
● Database
2.5 Determine the appropriate data recovery solution in Snowflake and how data can be
restored.
● Backup/Recovery
● Disaster Recovery
3.0 Domain: Data Engineering
3.1 Determine the appropriate data loading or data unloading solution to meet
business needs.
● Data sources
● Ingestion of the data
● Architecture Changes
● Data unloading
3.2 Outline key tools in Snowflake’s ecosystem and how they interact with
Snowflake.
● Connectors
○ Kafka
○ Spark
○ Python
● Drivers
○ JDBC
○ ODBC
● API endpoints
● SnowSQL
3.3 Determine the appropriate data transformation solution to meet business needs.
● Materialized Views, Views and Secure Views
● Staging layers and tables
● Querying semi-structured data
● Data processing
● Stored Procedures
● Streams and Tasks
● Functions
○ External Functions
○ User-Defined Functions
4.0 Domain: Performance Optimization
4.1 Outline performance tools, best practices, and appropriate scenarios where they
should be applied.
● Query profiling
● Virtual Warehouse configuration
● Clustering
● Search Optimization
● Caching
● Query rewrite
4.2 Troubleshoot performance issues with existing architectures.
● JOIN explosions
● Warehouse selection (scaling up as compared to scaling out)
● Best practices and optimization techniques
● Duplication of data
● Monitoring and Alerting
○ Statistics
○ Resource Monitoring
○ Account Usage and Information schema
