Building Data Analytics Solutions Using Amazon Redshift

In this course, you will build a data analytics solution using Amazon Redshift, a cloud data warehouse service. The course focuses on the data collection, ingestion, cataloging, storage, and processing components of the analytics pipeline.

This instructor-led training shows how Amazon Redshift is used to design and operate data warehouse analytics solutions on AWS. You learn how Redshift integrates with data lakes to support both analytics and machine learning workloads. Through presentations, interactive demos, and hands-on labs, the course also covers security, performance, and cost management best practices for operating Amazon Redshift in production environments.

Course objectives

In this course, you will learn to:

Compare the features and benefits of data warehouses, data lakes, and modern data architectures
Design and implement a data warehouse analytics solution
Optimize data storage using appropriate techniques such as compression
Select and deploy suitable options to ingest, transform, and store data
Choose appropriate instance and node types, clusters, auto scaling, and network topology
Understand how storage and processing affect analytics and visualisation
Secure data at rest and in transit
Monitor analytics workloads and remediate issues
Apply cost management best practices

Prerequisites

We recommend that attendees of this course have:

Completed either AWS Technical Essentials or Architecting on AWS
Completed Building Data Lakes on AWS

Students with at least one year of experience managing data warehouses will benefit from this course.

Target audience

This course is intended for:

Data warehouse engineers
Data platform engineers
Architects and operators who build and manage data analytics pipelines

Overview of data analytics and the data pipeline

You are introduced to analytics use cases and how data pipelines support analytics workloads.

Using Amazon Redshift in the analytics pipeline

This section explains why Amazon Redshift is used for data warehousing and how it fits into analytics architectures.

Introduction to Amazon Redshift

You explore Redshift architecture, core features, and work through labs loading and querying data in a Redshift cluster.

Ingestion and storage

The course covers ingestion techniques, data distribution and storage, querying semi-structured data, and working with Redshift Spectrum through hands-on labs.

Processing and optimising data

You work with data transformation, advanced querying, workload management, automation, and cluster optimisation, including resizing demonstrations.

Security and monitoring

This section focuses on securing Redshift clusters and monitoring and troubleshooting analytics workloads.

Designing data warehouse analytics solutions

The course concludes with reviewing data warehouse use cases, designing analytics workflows, and exploring modern data architectures on AWS.

Practical information

Duration: 1 day
Price: 9 900 NOK
Course level: Intermediate

FAQ

Er dette et sertifiseringskurs?
Nei, dette er et opplæringskurs og gir ingen formell sertifisering.

Er kurset praktisk rettet?
Ja, kurset inkluderer presentasjoner, interaktive demoer, praktiske laber, diskusjoner og klasseøvelser.

Hvilke AWS-tjenester jobber man med i kurset?
Kurset fokuserer hovedsakelig på Amazon Redshift, samt integrasjon med data lakes og relaterte AWS-tjenester.

Passer kurset for deltakere uten erfaring med data warehouses?
Noe erfaring med data warehouses anbefales for å få fullt utbytte av kurset.

Dekker kurset moderne dataarkitekturer?
Ja, kurset setter data warehouse-løsninger inn i konteksten av moderne dataarkitekturer på AWS.

Kursavgift:	9,900 NOK
Kurset inkluderer:	Course documentation and exercises. Lunch and refreshments for in class events only.
Timer	09:00 - 17:00
Varighet:	1 dager
Språk	Norwegian, English