This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. This course provides a detailed introduction to Snowflake's Data Cloud, focusing on fundamental concepts, best practices, and tools for leveraging Snowflake as a modern data warehouse solution.

Over three days, you will explore:

• Efficient Data Management: Learn to load, store, and transform structured and semi-structured data in Snowflake using SQL and Python for streamlined data workflows.
• Optimizing Query Performance: Develop skills to write efficient queries, leverage Snowflake's caching features, and use query profiling tools to improve performance and concurrency.
• Implementing Security and Governance: Gain expertise in configuring role-based access controls, managing authentication, and applying Snowflake's advanced data protection features like cloning and time travel.
• Integrating with Analytics Tools: Build the ability to connect Snowflake with popular BI tools such as Tableau and Power BI, enabling seamless reporting and data visualization.
• Real-World Application: Master end-to-end workflows, combining data loading, querying, transformation, and visualization to solve practical business challenges effectively.

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 professionals responsible for managing, analyzing, and architecting data solutions, including data analysts, data engineers, data scientists, database administrators, and architects. It's ideal for individuals who work with large datasets, design data-driven applications, or need to optimize workflows in a modern cloud environment. Whether you're looking to enhance your technical skills or streamline data processes for your organization, this course provides the practical knowledge and tools to succeed.

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

Morning Session

1. Introduction to Snowflake

• Key features and benefits of Snowflake.
• Understanding Snowflake's architecture (storage, compute, and cloud services).
• Navigating Snowsight and its interface.

2. Connecting to Snowflake

• Options for connecting (Snowsight, SnowSQL, Python connectors).
• Establishing secure connections.
• Hands-On Lab:
• Setting up a Snowflake account.
• Exploring the Snowflake interface and connection options.

3. Core Data Operations

• Introduction to Data Definition Language (DDL) and Data Manipulation Language (DML).
• Creating and managing tables and views.
• Writing basic SQL queries for data exploration.

4. Data Loading Basics

• Understanding data loading objects and formats.
• Loading data using the COPY command.
• Managing bulk data imports.
• Hands-On Lab:
• Creating tables and loading sample data into Snowflake.
• Writing simple queries to retrieve and analyze data.

Day 2: Querying, Caching, and Data Transformation

5. Advanced Querying

• Using window functions, groupings, and joins.
• Implementing estimation and sampling functions.
• Writing efficient queries with query tags and parameters.

6. Caching and Metadata Management

• Overview of Snowflake's caching layers (result and data cache).
• Understanding metadata for optimizing query performance.
• Hands-On Lab:
• Writing advanced SQL queries.
• Exploring query performance using Query Profile.

7. Data Transformation and Optimization

• Using Python to transform data in Snowflake.
• Managing and transforming semi-structured data (e.g., JSON).
• Optimizing queries for performance and concurrency.
• Hands-On Lab:
• Performing data transformations with Python.
• Querying and flattening semi-structured data.

Day 3: Security, Protection, and Integration

8. Data Security and Governance

• Overview of access control and authentication.
• Role-based access control (RBAC) and grants.
• Protecting data with encryption and masking.

9. Data Protection Features

• Cloning, time travel, and fail-safe recovery.
• Introduction to replication for disaster recovery.
• Hands-On Lab:
• Configuring roles and permissions.
• Exploring data protection with cloning and time travel.

10. Integration and Reporting

• Integrating Snowflake with BI tools (Tableau, Power BI).
• Exporting data for visualization and reporting.

11. End-to-End Workflow

• Combining loading, querying, and visualization in a real-world scenario.
• Hands-On Lab:
• Connecting Snowflake to a BI tool.
• Completing an end-to-end workflow: loading, querying, and visualizing data.