AWS Redshift – A Comprehensive Guide

A Comprehensive Guide on AWS Redshift – Fundamentals, Features and Management through Examples and Demos

Amazon Redshift is a fast, easy to use, cost-effective, peta-byte level, cloud based data warehousing solution. It promises to deliver up to 3x better price-performance than other cloud data warehouses. It takes advantage of AWS designed-hardware and machine learning (ML) to deliver the best price performance at any scale.

What you’ll learn

  • Redshift – Core Components and Features.
  • Loading and Querying Data – Query Editor, SQL Client Tools, BI Tools, CLI, APIs.
  • Automated Table Design, Data Distribution, Sorting and Workload Management.
  • Cluster Resizing, Relocation, Pause, Shutdown, Backup.
  • Security, Logging and Monitoring in Redshift.
  • Redshift Spectrum – Querying the Datalake.
  • Federated Queries – Querying RDS (relational database).
  • Redshift ML – Advanced analytics with Redshift & Sagemaker.
  • Stored Procedures, Materialized Views.

Course Content

  • Overview –> 5 lectures • 24min.
  • Getting Started –> 4 lectures • 40min.
  • How Redshift Works? –> 4 lectures • 26min.
  • Manage Data in Redshift –> 10 lectures • 1hr 9min.
  • Redshift and AWS services –> 4 lectures • 23min.
  • Manage Redshift Cluster –> 5 lectures • 50min.
  • Conclusion –> 2 lectures • 15min.

AWS Redshift - A Comprehensive Guide

Requirements

  • software engineering.
  • data warehousing experience.
  • SQL.

Amazon Redshift is a fast, easy to use, cost-effective, peta-byte level, cloud based data warehousing solution. It promises to deliver up to 3x better price-performance than other cloud data warehouses. It takes advantage of AWS designed-hardware and machine learning (ML) to deliver the best price performance at any scale.

The objective of the course is to understand redshift from an end to end perspective. The course is divided in following sections

  1. Overview – Brief introduction to Datawarehouse, Evolution and AWS redshift.
  2. Getting Started – We will get started on redshift where we will load and query sample data. We will understand what redshift created for us behind the scenes. we will also get familiar with the redshift console in this section.
  3. How does it work – We will jump into the core mechanics of redshift. we will understand the core components, functions of redshift which help in high performance and scalability.
  4. Manage Data – we will move to manage data section where we will understand the data types, data loading, data querying, data design with distribution and sort keys, stored procedures, materialized views and workload management in redshift.
  5. AWS Services – we are going to cover the integration aspects of redshift with other AWS services such as datalake formation, aws EMR, AWS glue, amazon kinesis, amazon quick sight, sagemaker, migration tools, etc. We will also understand the redshift spectrum and federated queries in this section.
  6. Manage Cluster – We will cover the cluster operations, snapshots, moniroting & security.
  7. Conclude – Pricing, Best Practices, Reading references.