Course Overview
Data Warehousing on AWS introduces concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift. The course covers the collection, storage, preparation, loading, analysis, and visualization of data within an AWS data warehousing environment.
Participants work with Amazon Redshift and supporting AWS services including Amazon S3, Amazon DynamoDB, Amazon EMR, Amazon Kinesis Data Firehose, AWS Lambda, and Amazon QuickSight. The course also covers database schema design, data loading, query performance tuning, workload management, Amazon Redshift Spectrum, cluster maintenance, monitoring, backup and restore operations, and data visualization.
Course Objective
- Discuss core data warehousing concepts and the relationship between data warehousing and big data solutions
- Launch and configure an Amazon Redshift cluster for cloud-based data warehousing
- Use Amazon Redshift features and functionality to implement a data warehouse
- Identify and use AWS data and analytics services that contribute to a data warehousing solution
- Design database schemas using appropriate data types, compression, distribution styles, and sorting methods
- Load and manage data in Amazon Redshift using appropriate data-loading techniques
- Identify query performance issues and apply query optimization and database tuning techniques
- Use Amazon Redshift Spectrum to analyze data stored in Amazon S3
- Maintain, monitor, back up, restore, and resize Amazon Redshift clusters
- Use Amazon QuickSight to analyze and visualize data from the data warehouse
Pre-requisites
- AWS Technical Essentials or equivalent AWS experience
- Familiarity with relational databases and database design concepts
Course Curriculum
