SAA-Exam Converage

Account and Security

Design a Snowflake account and database strategy, based on business requirements.

1. Create and configure Snowflake parameters based on a central account and any additional accounts.
2. List the benefits and limitations of one Snowflake account as compared to multiple Snowflake accounts.

Design an architecture that meets data security, privacy, compliance, and governance requirements.

1. Configure Role Based Access Control (RBAC) hierarchy
2. System roles and associated best practices
3. Data Access
4. Data Security
5. Compliance

Outline Snowflake security principles and identify use cases where they should be applied.

1. Encryption
2. Network security
3. User, Role, Grants provisioning
4. Authentication

Snowflake Architecture

Outline the benefits and limitations of various data models in a Snowflake environment.

1. Data models

Design data sharing solutions, based on different use cases.

1. Use Cases
   1. Sharing within the same organization/same Snowflake account
   2. Sharing within a cloud region
   3. Sharing across cloud regions
   4. Sharing between different Snowflake accounts
   5. Sharing to a non-Snowflake customer
   6. Sharing Across platforms
2. Data Exchange
3. Data Sharing Methods

Create architecture solutions that support Development Lifecycles as well as workload requirements.

1. Data Lake and Environments
2. Workloads
3. Development lifecycle support

Given a scenario, outline how objects exist within the Snowflake Object hierarchy and how the hierarchy impacts an architecture.

1. Roles
2. Warehouses
3. Object hierarchy
4. Database

Determine the appropriate data recovery solution in Snowflake and how data can be restored.

1. Backup/Recovery
2. Disaster Recovery

Data Engineering

Determine the appropriate data loading or data unloading solution to meet business needs.

1. Data sources
2. Ingestion of the data
3. Architecture Changes
4. Data unloading

Outline key tools in Snowflake’s ecosystem and how they interact with Snowflake.

1. Connectors
   1. Kafka
   2. Spark
   3. Python
2. Drivers
   1. JDBC
   2. OBDC
   3. API endpoints
   4. SnowSQL

Determine the appropriate data transformation solution to meet business needs.

1. Materialized Views, Views and Secure Views
2. Staging layers and tables
3. Querying semi-structured data
4. Data processing
5. Stored Procedures
6. Streams and Tasks
7. Functions

Performance Optimization

Outline performance tools, best practices, and appropriate scenarios where they should be applied.

1. Query profiling
2. Virtual Warehouse configuration
3. Clustering
4. Search Optimization
5. Caching
6. Query rewrite

Troubleshoot performance issues with existing architectures.

1. JOIN explosions
2. Warehouse selection (scaling up as compared to scaling out)
3. Best practices and optimization techniques
4. Duplication of data