Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift. This course demonstrates how to ingest, store, and transform data in the data warehouse. Topics covered include: the purpose of Amazon Redshift, how Amazon Redshift addresses business and technical challenges, features and capabilities of Amazon Redshift, designing a Data Warehousing Solution on AWS by applying best practices based on the Well-Architected Framework, integration with AWS and non-AWS products and services, performance tuning, orchestration, and securing and monitoring Amazon Redshift.
Course Objectives
In this course, you learn how to:
Describe Amazon Redshift architecture and its roles in a modern data architecture
Design and implement a data warehouse in the cloud using Amazon Redshift
Identify and load data into an Amazon Redshift data warehouse from a variety of sources
Analyze data using SQL QEV2 notebooks
Design and implement a disaster recovery strategy for an Amazon Redshift data warehouse
Perform maintenance and performance tuning on an Amazon Redshift data warehouse
Secure and manage access to an Amazon Redshift data warehouse
Share data between multiple Redshift clusters in an organization
Orchestrate workflows in the data warehouse using AWS Step Functions state machines
Create an ML model and configure predictors using Amazon Redshift ML
Intended AudienceÂ
This course is intended for:
Data engineers
Data architects
Database architects
Database administrators
Database developers
Prerequisites
We recommend that attendees of this course have completed the following prerequisites:
Fundamentals of Analytics on AWS – Part 1 (Digital course)
Fundamentals of Analytics on AWS – Part 2 (Digital course)
Building Data Lakes on AWS (Instructor led Training)
Building Data Analytics Solutions Using Amazon Redshift (Instructor led Training)
