Snowflake Training

Module 1: Introduction

Introduction to Snowflake

What is Snowflake?

Evolution of Data Warehousing

Traditional vs Cloud Data Warehousing

Snowflake Editions & Pricing

Key Features & Benefits

Real-world Use Cases

Snowflake vs Redshift vs BigQuery

Module 2: Architecture

Snowflake Architecture

Multi-cluster Shared Data Architecture

Database, Schema & Table Structures

Virtual Warehouses (Compute Layer)

Storage Layer (Micro-partitions)

Cloud Services Layer

Query Processing Flow

Result Caching & Metadata

Module 3: Security & Access Control

Users, Roles & Privileges

Role Hierarchy & Best Practices

RBAC (Role-Based Access Control)

Network Policies

Multi-Factor Authentication (MFA)

Data Encryption (At-rest & In-transit)

Column-level Security

Row Access Policies

Masking Policies

Module 4: Data Loading & Unloading

Internal & External Stages

File Formats (CSV, JSON, Parquet, Avro)

COPY INTO Command

Bulk Data Loading

Loading from AWS S3, Azure Blob

Error Handling & Validation

Data Unloading (Exporting Data)

Compression Techniques

Module 5: SQL & Data Transformation

DDL, DML, TCL Commands

Joins (Inner, Outer, Cross)

Subqueries & CTEs

Window Functions

Aggregations & Grouping

Stored Procedures

User Defined Functions (UDFs)

Views & Materialized Views

Data Transformation Techniques

Module 6: Performance Optimization

Query Performance Tuning

Warehouse Sizing & Scaling

Auto Suspend & Resume

Clustering Keys

Micro-partition Pruning

Caching (Result, Metadata, Warehouse)

Query Profile Analysis

Cost Optimization Techniques

Module 7: Data Sharing & Marketplace

Secure Data Sharing Concepts

Creating Shares

Consumer & Provider Accounts

Reader Accounts

Snowflake Data Marketplace

Cross-region Data Sharing

Module 8: Snowpipe & Automation

Introduction to Snowpipe

Continuous Data Ingestion

Event-based Triggers

Auto Ingest Setup

Monitoring Snowpipe

Error Handling

Module 9: Streams & Tasks

Change Data Capture (CDC)

Streams Concepts

Types of Streams

Tasks Scheduling

Building Data Pipelines

Automation Workflows

Module 10: Time Travel & Fail-safe

Time Travel Concepts

Data Recovery Techniques

Undrop Tables & Schemas

Retention Periods

Fail-safe Mechanism

Data Protection Strategies

Module 11: Semi-structured Data

Handling JSON, XML, Avro

VARIANT Data Type

Parsing Semi-structured Data

Flatten Function

Querying Nested Data

Best Practices

Module 12: Integration with Cloud Platforms

Integration with AWS S3

Integration with Azure Blob Storage

Integration with GCP

External Tables

Data Lake Integration

Module 13: Real-time Project

End-to-End Data Pipeline Design

ETL/ELT Implementation

Data Modeling (Star Schema)

Data Validation

Performance Optimization in Project

Deployment Strategies