This course combines engaging instructor-led presentations and practical hands-on labs to help participants build critical Snowflake skills.

By the end of this course, you will:

• Understand Snowflake's cloud-native architecture.
• Configure and manage virtual warehouses.
• Perform data loading using SnowSQL and SnowPipe.
• Apply caching and query optimization strategies.
• Analyze semi-structured data and create advanced queries.
• Integrate Snowflake with popular BI tools for visualization and reporting.
• Implement Snowflake's security features for data governance.
• Leverage Snowflake's collaboration and time travel features.
• Conduct end-to-end data analysis workflows for business use cases.

If your team requires different topics, additional skills or a custom approach, our team will collaborate with you to adjust the course to focus on your specific learning objectives and goals.

This course is tailored for IT professionals, developers, DevOps engineers, and data analysts responsible for building, managing, and optimizing data workflows. It's best suited for participants with technical backgrounds and basic SQL knowledge who want to enhance their skills in Snowflake for advanced data management and analysis.

Please note that this list of topics is based on our standard course offering, evolved from typical industry uses and trends. We'll work with you to tune this course and level of coverage to target the skills you need most. Topics, agenda and labs are subject to change, and may adjust during live delivery based on audience skill level, interests and participation.

Day 1: Snowflake Fundamentals

1. Introduction to Snowflake

• Key features and benefits of Snowflake.
• Overview of Snowflake's functional and technical architecture.

2. Getting Started with Snowflake

• Setting up accounts and exploring Snowsight.
• Hands-On Lab
• Configuring Snowflake and navigating its interface.

3. Working with Virtual Warehouses

• Creating and managing virtual warehouses.
• Scaling considerations and query design best practices.

4. Introduction to SnowSQL

• Installation, configuration, and basic commands.
• Hands-On Lab
• Creating virtual warehouses and loading data using SnowSQL.

Day 2: Advanced Features and Optimization

5. Advanced Querying and Performance Tuning

• Performing DDL and DML operations.
• Analyzing query performance with Query Profile.

6. Caching in Snowflake

• Using query result cache and warehouse data cache effectively.
• Hands-On Lab
• Writing advanced queries and analyzing performance metrics.

7. Working with Semi-Structured Data

• Loading and querying JSON, XML, and Parquet.
• Using FLATTEN for nested data structures.

8. Time Travel and Data Recovery

• Exploring time travel for historical analysis.
• Implementing data cloning for recovery scenarios.
• Hands-On Lab
• Querying semi-structured data and leveraging time travel features.

Day 3: Data Analysis and End-to-End Use Case

9. Advanced Data Analysis in Snowflake

• Using analytical functions like window functions and grouping sets.
• Querying large datasets efficiently.

10. Data Transformation and Enrichment

• Transforming and enriching data with Snowflake's SQL capabilities.
• Hands-On Lab
• Conducting advanced analysis and preparing datasets for enrichment.

11. Putting It All Together: End-to-End Use Case: Business Analytics Workflow

• Problem Definition: Analyzing a real-world dataset.
• Data Ingestion: Loading and preparing the dataset.
• Querying and Transformation: Extracting insights and preparing reports.
• Visualization: Creating dashboards and presenting findings.