Course Overview
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.
Who should attend
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 courses:
- Fundamentals of Analytics on AWS – Part 1 (Digital course)
- Fundamentals of Analytics on AWS – Part 2 (Digital course)
- Building Data Lakes on AWS Building Data Lakes on AWS (BDLA) (Instructor led Training)
- Building Data Analytics Solutions Using Amazon Redshift ! (Instructor led Training)
Course Objectives
In this course, you will learn 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
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