Amazon Web Services (AWS) - Building Data Analytics Solutions Using Amazon Redshift

Overview

On this accelerated Building Data Analytics Solutions Using Amazon Redshift course, you will build a data analytics solution using Amazon Redshift, a cloud data warehouse service.

The course focuses on the data collection, ingestion, cataloguing, storage, and processing components of the analytics pipeline. You will learn to integrate Amazon Redshift with a data lake to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon Redshift. Activities

This course includes presentations, interactive demos, practice labs, discussions, and class exercises

Upon completion of this course you will be able to:

• Compare the features and benefits of data warehouses, data lakes, and modern data architectures
• Design and implement a data warehouse analytics solution
• Identify and apply appropriate techniques, including compression, to optimize data storage
• Select and deploy appropriate options to ingest, transform, and store data
• Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case
• Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights
• Secure data at rest and in transit
• Monitor analytics workloads to identify and remediate problems
• Apply cost management best practices

At the end of this course, you’ll sit achieve your Building Data Analytics Solutions Using Amazon Redshift certification.

Through Firebrand’s Lecture | Lab | Review methodology you’ll certify at twice the speed of traditional training and get access to courseware, learn from certified instructors, and train in a distraction-free environment.

40% faster

Distraction-free environment

Audience

This course is ideal for data warehouse engineers, data platform engineers, and architects and operators who build and manage data analytics pipelines.