Snowflake Fundamentals | Cloud Data Training

Snowflake Fundamentals Training Outline

Learning Objectives

Data Warehousing Overview

• Data warehousing evolution
• Cloud data warehousing
• Adapting to increasing demands for data access and analytics
• Adjusting to how data is created and used today
• Architecture and Overview

Technical Overview

• Cloud Services Layer
• Compute Layer
• Storage Layer
• Architecture Deep Dive

Optimization

• Security
• Tokenization
• Best Practices
• Data Movement

Data Loading

• Data Unloading
• Best Practices
• Data Sharing
• Snowpipe
• Objects and Commands

Query Constructs

• Data Description Language (DDL)
• Data Manipulation Language (DML)
• Local only resources
• SQL Support for Data Analysis

SQL Support and Query Best Practices

• SQL Analytic Functions
• High Performing Estimation Functions
• UDF and Stored Procedure
• Demo Query Profile
• Managing Security

Data Encryption

• Authentication
• Role-Based Access Control
• Semi-structured data

Working with semi-structured data

• Queries
• Data Optimization
• Caching

Caching Features

• Performance Improvements
• Cost Optimization
• Clients and Ecosystem

Clients

• Connectors
• SnowSQL
• Security

Continuous Data Protection

• Time Travel
• Fail Safe
• Cloning
• Performance and Concurrency

Query Profile

• Micro-Partitions
• Data Clustering
• Scaling a Virtual Warehouse
• Account and Resources Management and Monitoring

System Resource Usage and Billing

• Managing Virtual Warehouses
• Workload Independence and Segmentation
• Resource Monitors
• Information Schema and Account Usage