Snowflake

Location: On-Site or Online
Pricing: $1,250 per seat (6-seat minimum)
Length: 4 Days

Course Summary

Snowflake is a practical, hands-on course designed to teach students how to design, operate, and optimize modern cloud data platforms using Snowflake.

Students learn how Snowflake works under the hood—from virtual warehouses and storage layers to security, data sharing, and performance optimization. The course emphasizes real-world data workflows including ingestion, transformation, querying, governance, and cost control.

By the end of the course, students are comfortable loading data into Snowflake, querying it efficiently, managing users and roles, and supporting analytics and data engineering workloads in production environments.

Course Outline

Day 1 – Snowflake Architecture and Core Concepts

• 💬 Lecture: Modern data platforms and why Snowflake exists

• 💬 Lecture: Snowflake architecture (storage, compute, cloud services)

• 💬 Lecture: Accounts, organizations, and regions

• 💬 Lecture: Virtual warehouses and scaling models

• 💬 Lecture: Snowflake editions and pricing fundamentals

• ⚙️ Lab: Accessing a Snowflake account and web UI

• ⚙️ Lab: Exploring databases, schemas, and tables

• ⚙️ Lab: Creating and managing virtual warehouses

• ⚙️ Lab: Running basic SQL queries

• ⚙️ Lab: Observing warehouse scaling and suspension behavior

Day 2 – Data Loading, Storage, and Querying

• 💬 Lecture: Snowflake data types and table structures

• 💬 Lecture: Stages, file formats, and data loading workflows

• 💬 Lecture: COPY INTO and bulk ingestion patterns

• ⚙️ Lab: Creating internal and external stages

• ⚙️ Lab: Loading structured data into Snowflake

• ⚙️ Lab: Loading semi-structured data (JSON)

• ⚙️ Lab: Querying semi-structured data with VARIANT

• 💬 Lecture: Query processing and optimization basics

• ⚙️ Lab: Understanding query profiles

• ⚙️ Lab: Improving query performance

• ⚙️ Lab: Using clustering and micro-partition awareness

Day 3 – Security, Governance, and Data Engineering

• 💬 Lecture: Users, roles, and role hierarchy

• 💬 Lecture: Authentication and access control

• 💬 Lecture: Data governance and compliance features

• ⚙️ Lab: Creating users and roles

• ⚙️ Lab: Granting privileges using RBAC

• ⚙️ Lab: Restricting access to sensitive data

• 💬 Lecture: Data engineering features in Snowflake

• 💬 Lecture: Streams, tasks, and change data capture

• ⚙️ Lab: Creating streams to track data changes

• ⚙️ Lab: Building scheduled tasks

• ⚙️ Lab: Automating data transformations

• 💬 Lecture: Secure data sharing

• ⚙️ Lab: Sharing data across accounts

• ⚙️ Lab: Consuming shared datasets

Day 4 – Performance, Cost, and Real-World Workflows

• 💬 Lecture: Performance tuning and workload isolation

• 💬 Lecture: Cost management and usage monitoring

• ⚙️ Lab: Monitoring warehouse usage

• ⚙️ Lab: Identifying expensive queries

• ⚙️ Lab: Optimizing warehouse sizing

• 💬 Lecture: Integrating Snowflake with external tools

• 💬 Lecture: Snowflake in analytics and ML workflows

• ⚙️ Lab: Connecting Snowflake to BI tools

• ⚙️ Lab: Exporting data from Snowflake

• 💬 Lecture: Best practices for production Snowflake environments

• ⚙️ Lab: Designing a complete Snowflake data workflow

• ⚙️ Lab: Combining ingestion, transformation, and querying

• ⚙️ Lab: Validating data accuracy and performance

Outcomes

Students who complete Snowflake will be able to:

• Explain Snowflake architecture and scaling behavior

• Load and query structured and semi-structured data

• Manage users, roles, and secure access

• Build automated data pipelines using Snowflake features

• Optimize performance and control costs

• Apply Snowflake best practices in real production environments