This course prepares attendees to take the SnowPro Advanced Architect exam. The advanced-level certification validates the skills and knowledge required to apply comprehensive architect solutions using Snowflake. This class covers data flow design, selection of appropriate tools, deployment of shared data sets, and architecting for business needs.
| Duration |
Delivery Method |
Mandatory Prerequisites |
Who Should Attend |
| 3 days |
Virtual – Intructor led |
- Attendees should have:
- Completed the Snowflake Fundamentals training or have equivalent experience
- Ideally, achieved the SnowPro Core Certification
|
The audience for this class is data developers, data engineers, data architects, and database administrators and Data Warehouse knowledge. |
Course Objectives:
Attendees will leave understanding advanced Snowflake architecture and features such as partitioning, clustering, materialized views, time travel, and data sharing. Learn techniques for optimizing query performance, such as query profiling, query optimization, and caching. Data modeling and integration techniques, including schema design, data ingestion, data transformation, and data quality. Snowflake’s security and compliance features, including access control, authentication, encryption, and auditing. They will also learn best practices and design patterns for designing and implementing Snowflake solutions, including data warehousing, data lakes, and real-time data pipelines.
Agenda:
Snowflake Accounts and Security
- Snowflake account and database strategy
- Snowflake’s security features
- Managing user accounts and roles and implementing governance policies and procedures
- Data security best practices
- Encrypting data in Snowflake
- Network Security
- User, role, grants provisioning
Snowflake Virtual Warehouses
- Understanding Snowflake’s virtual warehouse concept i.e., Data Isolation, Concurrent workloads
- Creating and managing virtual warehouses
- Scaling virtual warehouses for performance optimization
- Troubleshooting virtual warehouse issues
Snowflake Architecture
- Snowflake architecture
- Benefits and limitations of various data models in the Snowflake environment
- Data Sharing solutions
- Snowflake object architecture and its impacts on architecture
- Data recovery
- Understanding Snowflake’s deployment models (public cloud, private cloud, hybrid)
- Understanding Snowflake’s data storage and virtual warehouse concepts
- Introduction to Snowflake’s administration and monitoring tools
- Caching Features
- Performance Improvements
- Cost Optimization
|
Data Engineering
- Understanding Snowflake’s data loading methods (bulk loading, streaming, etc.)
- Integrating Snowflake with other data sources using connectors and APIs
- Data transformation and preparation in Snowflake
- Best practices for data ingestion and integration with Snowflake
Snowflake Data Storage
- Understanding Snowflake’s data storage concepts
- Managing Snowflake data storage
- Using Snowflake tables and schemas
- Managing metadata in Snowflake
Snowflake Querying and Materialized Views
- Querying data in Snowflake
- Advanced querying techniques in Snowflake
- Performance tuning and optimization strategies in Snowflake
- Understanding materialized views in Snowflake
- Creating and managing materialized views
- Using materialized views for query optimization
- Troubleshooting materialized view issues
|
Snowflake Advanced Features
- Introduction to advanced features of Snowflake
- Using external functions in Snowflake
- Automating data workflows with Snowflake tasks
- Managing data streams in Snowflake
- Time Travel
Snowflake Data Sharing
- Overview of Snowflake’s data-sharing features
- Sharing data across accounts and organizations
- Managing data-sharing activities in Snowflake
Performance Optimization
- Query profiling
- Clustering
- Search optimization service
- Resource Monitors
- Information Schema and Account Usage
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