❄️ Snowflake

Comprehensive Snowflake Data Cloud Training

🕒 Course Duration: 50 Hours (Across 45 Days)

🎯 Target Audience:

• Freshers

• Data Engineers

• Data Analysts

• BI Developers

• Cloud Engineers

• Anyone interested in modern data warehousing

📘 Course Objectives:

• Understand Snowflake architecture and its advantages

• Learn scalable, cloud-native data warehousing techniques

• Explore data loading, transformation, and querying workflows

• Implement access control, security, and cost optimization

• Work with semi-structured data, tasks, and automation

• Integrate with tools like DBT, Python, Streamlit, and Snowpark

📚 Modules & Topics Covered

🔹 Module 1: Introduction to Snowflake

• What is Snowflake?

• Evolution of Cloud Data Warehousing

• Snowflake vs Traditional DWH

• Editions & Pricing Models

• Supported Cloud Platforms (AWS, Azure, GCP)

🔹 Module 2: Snowflake Architecture

• Cloud Services Layer

• Virtual Warehouses

• Storage Architecture

• Shared Disk vs Shared Nothing

🔹 Module 3: Getting Started

• Trial Account Setup

• Snowflake UI, Snowsight, and Worksheets

• User & Role Management

🔹 Module 4: Database Objects

• Tables: Permanent, Transient, Temporary

• Views: Standard, Secure, Materialized

• Sequences, Stages, File Formats

🔹 Module 5: Data Loading & Unloading

• Internal vs External Stages

• File Formats: CSV, JSON, Parquet, etc.

• COPY INTO, Snowpipe, and Unloading Data

🔹 Module 6: SQL & Querying

• DDL, DML, TCL commands

• Joins, CTEs, Subqueries

• Time Travel and Fail-safe features

🔹 Module 7: Security & Access Control

• Role-Based Access Control (RBAC)

• Creating Users, Roles, Privileges

• Network Policies, MFA, SSO

• Masking & Row Access Policies

🔹 Module 8: Performance Optimization

• Caching: Metadata, Results, Queries

• Warehouse Sizing & Scaling

• Query Profiling and Optimization

🔹 Module 9: Semi-Structured Data

• JSON, Avro, ORC, XML

• VARIANT, FLATTEN, Nested Queries

🔹 Module 10: Streams, Tasks, & Automation

• Change Data Capture with Streams

• Tasks for SQL Scheduling

• Pipeline Automation

🔹 Module 11: Data Sharing & Marketplace

• Secure Data Sharing

• Provider/Consumer Models

• Reader Accounts & Marketplace Usage

🔹 Module 12: Integrations & Ecosystem

• BI Tools (Power BI, Tableau, Looker)

• DBT, Snowpark (Python), Airflow, Kafka

• Intro to Streamlit for Data Applications

🔹 Module 13: Streamlit Integration

• Build interactive dashboards with Snowflake data

• Authentication via Snowpark

• Charts, filters, search, monitoring dashboards

• Deploying Streamlit apps

🔹 Module 14: AI & ML with Snowflake Cortex

• Snowflake Copilot, Cortex LLM Functions

• Document AI, Search, Analyst

• Fine-tuning & Insights generation

🔹 Module 15: Advanced Features

• Materialized Views, External Tables

• Search Optimization & Query Acceleration

🔹 Module 16: Monitoring & Cost Management

• Resource Monitors, Usage Dashboard

• Credit & Cost Optimization

🔹 Module 17: Hands-On Projects

• ELT Pipeline Building

• Real-time Ingestion (Snowpipe + Tasks)

• Streamlit-based Analytics Dashboard

🔹 Module 18: AWS Integration

• Amazon S3 Integration

• External stages for loading/unloading

• Snowpipe with IAM Roles

• SQS/SNS configuration

📝 Assessment & Certification Guidance

• Sample Exam Questions

• Certification Pathway

• Resume Tips for Snowflake Roles

• Interview Preparation Support

✅ Outcome:

By the end of the training, participants will be able to build, optimize, and manage cloud-native data pipelines and analytics solutions using Snowflake — with strong readiness for job roles in modern data engineering, analytics, and cloud platforms.