Master Snowflake 2024

Course Curriculum

Chapter 1: Introduction

Lecture 1: What is Snowflake?

Lecture 2: Snowflake architecture

Lecture 3: Database Storage and compute

Lecture 4: Services Layer

Lecture 5: Setup a free trial

Lecture 6: Login to snowflake account

Chapter 2: *** SNOWFLAKE INFRASTRUCTURE ***

Lecture 1: Introduction

Chapter 3: Snowsight

Lecture 1: Snowsight – Snowflake web interface

Lecture 2: Getting Started with Worksheets

Lecture 3: Sort, filter, show stats of query results

Lecture 4: Visualizing data in worksheet

Lecture 5: Create your first warehouse

Lecture 6: Creating a warehouse via SQL

Lecture 7: Databases > Schemas > Tables

Chapter 4: Snowflake Hierarchy and Objects

Lecture 1: Snowflake Container System

Lecture 2: Database > Schema objects

Lecture 3: Creating Database > Schemas

Lecture 4: Create a table

Lecture 5: inserting data into table via INSERT

Lecture 6: Table with text data types

Lecture 7: Table with boolean values

Lecture 8: Table with timestamps

Lecture 9: Create table via SELECT

Lecture 10: Snowflake constraints handling

Chapter 5: **** DATA LOADING ****

Lecture 1: Introduction

Chapter 6: Data Loading

Lecture 1: Bulk/Continuous loading methods

Lecture 2: Internal/External stages

Chapter 7: Loading data from AWS

Lecture 1: Setup a free trial

Lecture 2: Create a S3 bucket

Lecture 3: Upload data to S3 bucket

Chapter 8: Loading data from Azure

Lecture 1: Creating a free trial

Lecture 2: Create a storage account

Lecture 3: Create storage containers

Lecture 4: Setup an integration object

Lecture 5: Configure a role assignment

Lecture 6: Create stage objects

Lecture 7: Load CSV file

Lecture 8: Load JSON file

Lecture 9: Load JSON data into variant column

Chapter 9: Loading data from Google Cloud

Lecture 1: Create a free trial

Lecture 2: Create a storage object

Lecture 3: Create an integration object

Lecture 4: Create stages

Lecture 5: Query and load the data

Chapter 10: Working wiht JSON data

Lecture 1: JSON File data classification

Lecture 2: Insert data into table

Lecture 3: Query JSON data

Lecture 4: Query nested JSON data

Lecture 5: Apply functions to JSON objects

Lecture 6: Flatten JSON data

Lecture 7: JSON data to tabular format

Chapter 11: Micro-partitions

Lecture 1: Introduction to Micro-partition

Lecture 2: Snowflake micro-partition advantages

Lecture 3: The columnar storage system

Lecture 4: Partition Types and I/O operations

Lecture 5: How micro-partitions work?

Chapter 12: Data Clustering

Lecture 1: What is data clustering?

Lecture 2: Clustering Keys

Lecture 3: Create cluster keys, query performances

Lecture 4: Alter/Drop cluster keys

Chapter 13: Views

Lecture 1: Non-Materialized view

Lecture 2: Combining views together

Lecture 3: What is a Materialized View?

Lecture 4: When to create or not create a materialized view?

Lecture 5: Creating and analyzing materialized views performances

Lecture 6: Important metadata columns

Lecture 7: Are views dynamic?

Lecture 8: Are materialized views dynamic?

Lecture 9: Table Alter effect on materialized view

Lecture 10: Data updates on standard and materialized views

Lecture 11: Materialized views limitations

Lecture 12: Limitations of views

Lecture 13: How to create a recursive view?

Chapter 14: Data Sampling Techniques

Lecture 1: What is data sampling?

Lecture 2: Data sampling methods

Lecture 3: Using ROW and SYSTEM methods

Lecture 4: Using SEED to compare data records

Chapter 15: Snowflake Tasks

Lecture 1: Creating a task

Lecture 2: Alter, clone a task, review history

Lecture 3: Understand schedule parameter

Lecture 4: Using CRON

Lecture 5: Creating a serverless task

Lecture 6: Task tree

Lecture 7: calling a stored procedure

Lecture 8: Task with conditions