Snowflake Fundamentals

Snowflake Fundamentals

Snowflake

Course Description

Snowflake is a cloud-based data warehouse and analytical tool. With so many SaaS Data warehouse solutions available competing against one another, Snowflake stands out among the crowd for its uniqueness in design and approach. This course helps candidates prepare for the SnowPro Core Certification.

Duration Delivery Method Mandatory Prerequisites Who Should Attend
4 days Virtual – Intructor led
  • Attendees should have Data Warehouse knowledge
The audience for this class is Data Analysts, Data Engineers, Data Scientists, Data Architects, and Database Administrators.

Course Objectives:

Attendees will leave understanding the Snowflake architecture, how to load and transform data, and how to evaluate query constructs, DDL and DML Operations. They will also learn how to manage application and user access, learn best practices for working with semi-structured data, and employ Snowflake’s method for continuous data protection. This course will also serve as preparation for the SnowPro Core Certification.

Agenda:

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