Building Data Analytics Solutions Using Amazon Redshift
This 1-day course explores the analytics capabilities of Amazon Redshift.
In this 1-day course, you will learn how to build a data analytics solution using Amazon Redshift, a cloud data warehouse.
The course covers important aspects of the analytics pipeline, including data collection, ingestion, cataloging, storage, and processing. You will discover how to integrate Amazon Redshift with a data lake to support analytics and machine learning tasks. Additionally, you will learn best practices for security, performance, and cost management when using Amazon Redshift.
The course is designed for individuals with intermediate knowledge and is suitable for data warehouse engineers, data platform engineers, and architects who manage data analytics pipelines. To benefit from this course, participants should have at least one year of experience in managing data warehouses and should have completed either AWS Technical Essentials or Architecting on AWS, as well as the Building Data Lakes on AWS course.
The training includes various activities such as presentations, interactive demos, practice labs, discussions, and exercises.
Throughout the course, you will compare the features of data warehouses and data lakes, design and implement a data warehouse analytics solution, optimize data storage, and select the right options for data ingestion and transformation. You will also learn how to choose the right instance types and clusters for specific business needs, secure data, monitor analytics workloads, and apply cost management strategies.