Course Overview
This four-day course covers the core concepts, design considerations, and Snowflake recommended best practices intended for critical stakeholders who will be working on the Snowflake AI Data Cloud. The course consists of lectures, demos, and labs covering a wide range of essential topics.
What are the skills covered
- Outline the unique and differentiated architecture of the Snowflake AI Data Cloud.
- Load and transform data.
- Summarize query constructs, DDL, and DML operations.
- Use Snowflake’s extensive SQL capabilities for data analysis.
- Describe how user and application access can be easily managed.
- Apply Snowflake’s recommended best practices for working with semi-structured data.
- Discuss Snowflake’s unique approach to caching.
- Implement the options provided to connect and interact with the Snowflake AI Data Cloud.
- Employ Snowflake’s continuous data protection features.
- Utilize data sharing to send your data in real-time to Customers and Partners.
- Scale your Virtual Warehouses to improve performance and address concurrency needs.
- Explain the different ways you can manage and monitor your Snowflake account.
- Summarize Snowflake’s AI and ML capabilities.
Who should attend this course
- Data Analysts
- Data Engineers
- Data Scientists
- Database Architects
- Database Administrators
Course Curriculum
Course Modules
Exam & Certification
SnowPro Advanced: Architect Certification Exam ARA-C01
SNOWPRO ADVANCED: ARCHITECT OVERVIEW
This certification will test the ability to:
- Design an end-to-end data flow from source to consumption using the Snowflake 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 Marketplace and Data Exchange
