Introduction to Redshift

Overview

Master Amazon Redshift's SQL, data management, optimization, and security.

This course offers a foundational understanding of Amazon Redshift, a distributed columnar database within the AWS cloud. Explore its integration into the AWS ecosystem and its SQL constructs, including common table expressions and analytics queries. Learn to create tables, manage data distribution, handle raw data files, and extract information from JSON. Additionally, optimize queries, tune performance, and enhance data security. By the end of the course, you'll have a strong command of SQL on Redshift and the knowledge and skills needed to use Redshift effectively.

Syllabus

Redshift, a data warehouse

Meet Redshift, a robust columnar data warehouse. We'll explore how columnar and typical data warehouses differ, what makes Redshift unique, how it fits into the AWS and data warehouse ecosystems, and what data types it supports.

SQL on Redshift

Let's learn about some nuances with Redshift SQL syntax, a close cousin of PostgreSQL's syntax. We compare CTEs and subqueries before moving into mastering date and time, exploring window queries, and wrapping up learning how transactions affect some functions.

Tables and working with semi-structured data

We'll explore how to create tables, the impact DISTKEY and SORTKEYs have on performance, external schemas/tables with Spectrum and wrap up with handling semi-structured data like JSON with Redshift.

Optimization and Security

It is time to peak into the world of writing optimized queries and tools available to help optimize. Then, we turn our attention to Redshift security capabilities and how they can impact query output.