Snowflake Masterclass[stored proc+demos+Best practices+Labs]

Based on the overview provided, here's a more detailed breakdown of what each module covers and the key topics within those modules for learning Snowflake effectively.

Module #1: Snowflake Environment Setup & Architecture

• Snowflake Environment Setup:

  • Installing and configuring Snowflake.
  • Creating a new Snowflake account and warehouse.
  • Understanding the interface (Snowflake Web UI and Snowflake Studio).
  • Initial database, schema, and table setup.

• Snowflake Architecture:

  • Explanation of the Snowflake architecture: data storage, query processing, and how it separates compute and store.
  • Overview of the Storage Integrated (SI) system and its components.
  • Understanding the differences between Fact and Dimension tables.

• Snowflake Caching, Micro-Partitions, Clusters:

  • How caching works in Snowflake.
  • Utilizing micro-partitions to optimize storage and performance.
  • Configuring and understanding clusters for better query performance.

• Snowflake Clustering Deep Dive:

  • Detailed explanation of clustering in Snowflake and how it affects query performance.
  • Best practices for cluster configuration.

• Virtual Warehouse Layer:

  • Understanding the concept of virtual warehouses and how they provide elasticity and resource sharing.
  • How to monitor and manage warehouse usage and costs.

• Performance Tuning and DB Characteristics:

  • Tips and techniques for optimizing performance within Snowflake.
  • Exploring database characteristics and their impact on query execution and performance.

Module #2: Loading Data in Snowflake

• Loading Data with Internal Stage:

  • How to use the internal stage for loading data.
  • Best practices for staging data before loading into tables.

• Loading Data from Various Sources:

  • Detailed walkthrough of loading data from AWS S3, Google GCS, and Azure Blob Storage using the COPY command.
  • Understanding the COPY command options for different sources.

• Working with COPY Command:

  • Hands-on experience with the COPY command to load data into Snowflake tables.
  • Exploring advanced COPY command features such as file format specifications, compression handling, and more.

• Assignments:

  • Practical exercises to apply knowledge of loading data into Snowflake.

• Loading Unstructured Data:

  • Techniques for loading and processing unstructured data in Snowflake.

Module #3: Advanced Snowflake Features & Data Integration

• Snowpipe in Snowflake:

  • Understanding Snowpipe and its role in continuously loading data from supported sources like Kafka, S3, or HTTP endpoints.

• Data Sharing in Snowflake:

  • Exploring the capabilities of sharing data within an organization securely across different Snowflake accounts.

• Time Travel:

  • Learning how Snowflake's Time Travel feature allows you to query past versions of data.

• Fail Safe:

  • Understanding how failover and fail safe work in Snowflake to ensure high availability.

• Clone Feature:

  • Learning how to use the clone feature for rapid provisioning and scaling of Snowflake databases, schemas, and tables.

• Data Sampling:

  • Understanding how to sample data within Snowflake for quality checks, testing, or privacy reasons.

• Tasks in Snowflake:

  • Exploring Snowflake tasks for automating routine workloads like data loading, transformation, and more.

• Streaming in Snowflake:

  • Learning about change data capture (CDC) and how to stream data changes in real-time.

• Continuous Data Load:

  • Setting up continuous data load mechanisms with Snowpipe or other streaming services.

• Materialized Views:

  • Understanding materialized views and how they can be used for caching query results to improve performance.

By the end of these three modules, you should have a comprehensive understanding of how to set up, use, and optimize your Snowflake environment, as well as a deep knowledge of the advanced features available for integrating, loading, and managing data within Snowflake.