Building Data Analytics Solutions using Amazon Redshift

Price
$675.00 USD

Duration
1 Day

 

Delivery Methods
Virtual Instructor Led
Private Group

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Course Overview

By 2025, the global data volume is expected to exceed 180 zettabytes—much of it requiring real-time insights. Amazon Redshift is a cornerstone of modern data analytics solutions, and this course teaches you how to harness its full power.

In this hands-on, instructor-led AWS course, you’ll learn to design, optimize, and scale data analytics solutions using Amazon Redshift. You’ll explore Redshift’s architecture, load and model data, run complex queries, and extend your reach with Redshift Spectrum and federated queries. Each module includes practical labs to reinforce skills you can apply in real cloud environments.

Course Objectives

This course prepares you to build scalable, cost-effective, and performance-optimized data analytics solutions on Amazon Redshift. You’ll gain hands-on experience loading, querying, and securing large datasets, and learn to integrate Redshift into broader AWS analytics workflows.

By the end of the course, you will be able to:

  • Understand Amazon Redshift architecture, key components and node types
  • Load, model, and query data with Redshift SQL
  • Use Redshift Spectrum and federated queries for external access
  • Apply cost management to enhance Redshift performance and efficiency

Who Should Attend?

This course is intended for data warehouse engineers, data platform engineers, and architects and operators who build and manage data analytics pipelines.
  • Top-rated instructors: Our crew of subject matter experts have an average instructor rating of 4.8 out of 5 across thousands of reviews.
  • Authorized content: We maintain more than 35 Authorized Training Partnerships with the top players in tech, ensuring your course materials contain the most relevant and up-to date information.
  • Interactive classroom participation: Our virtual training includes live lectures, demonstrations and virtual labs that allow you to participate in discussions with your instructor and fellow classmates to get real-time feedback.
  • Post Class Resources: Review your class content, catch up on any material you may have missed or perfect your new skills with access to resources after your course is complete.
  • Private Group Training: Let our world-class instructors deliver exclusive training courses just for your employees. Our private group training is designed to promote your team’s shared growth and skill development.
  • Tailored Training Solutions: Our subject matter experts can customize the class to specifically address the unique goals of your team.

What is the Building Data Analytics Solutions Using Amazon Redshift course?

This classroom training teaches you how to design, build, and optimize data analytics solutions on AWS using Amazon Redshift. The course dives deep into Redshift architecture, node types, data ingestion, and integration with external data sources to help you build scalable, real-time analytics pipelines.

Is the Building Data Analytics Solutions Using Amazon Redshift course worth it?

Yes—this course benefits professionals involved in building and operating data analytics solutions, particularly data platform engineers and architects. With hands-on labs and real-world use cases, it delivers actionable insight into query optimization, cluster management, and cost management strategies.

How does Amazon Redshift simplify data warehouse and analytics management?

Amazon Redshift simplifies operations by automating provisioning, auto scaling, backups, and workload optimization. It supports integration with data lakes, semi-structured data, and external catalogs, allowing you to build a modern, unified data warehouse that powers scalable analytics solutions.

How can this course help with business intelligence or analytics tasks?

You’ll learn to design pipelines that turn data into insights, build secure and efficient data analytics pipelines, and connect Redshift to machine learning and BI tools. The course covers best practices for performance, scaling, and optimization—ideal for delivering fast, flexible analytics across your organization.

Course Prerequisites

Students with a minimum one-year experience managing data warehouses will benefit from this course.

Agenda

Module A: Overview of Data Analytics and the Data Pipeline

  • Explore common use cases for data analytics
  • Understand how the data pipeline supports analytics at scale

Module 1: Using Amazon Redshift in the Data Analytics Pipeline

  • Learn why Amazon Redshift is used for cloud data warehousing
  • Get an overview of Amazon Redshift’s core capabilities

Module 2: Introduction to Amazon Redshift

  • Understand the architecture and components of Amazon Redshift
  • Interactive Demo 1: Navigate the Amazon Redshift console
  • Explore key Redshift features and functionalities
  • Practice Lab 1: Load and query data in a Redshift cluster

Module 3: Ingestion and Storage

  • Discover methods for ingesting data into Amazon Redshift
  • Interactive Demo 2: Connect to a Redshift cluster using a Jupyter notebook with the Data API
  • Learn how Redshift handles data distribution and storage
  • Interactive Demo 3: Work with semi-structured data using the SUPER data type
  • Explore how Redshift supports efficient querying across storage types
  • Practice Lab 2: Analyze data using Amazon Redshift Spectrum

Module 4: Processing and Optimizing Data

  • Perform data transformations using SQL in Amazon Redshift
  • Apply advanced querying techniques for complex analytics workloads
  • Practice Lab 3: Transform and analyze data in Redshift
  • Manage resources with workload management (WLM) features
  • Interactive Demo 4: Apply mixed workload management settings
  • Automate and optimize performance in Redshift environments
  • Interactive Demo 5: Resize clusters from dc2.large to ra3.xlplus

Module 5: Security and Monitoring of Amazon Redshift Clusters

  • Implement best practices for securing your Redshift cluster
  • Monitor cluster performance and troubleshoot issues effectively

Module 6: Designing Data Warehouse Analytics Solutions

  • Review real-world data warehouse scenarios
  • Activity: Design a modern analytics workflow using Redshift

Module B: Developing Modern Data Architectures on AWS

  • Examine patterns for building modern data architectures on AWS
  • Understand how Redshift fits into broader analytics and data lake ecosystems
  • Explore how Redshift integrates with machine learning tools like Amazon SageMaker for predictive insights
 

Upcoming Class Dates and Times

Jul 2
6:30 AM - 2:30 PM
ENROLL $675.00 USD
Guaranteed to Run
Virtual: Online - PST
Sep 4
6:30 AM - 2:30 PM
ENROLL $675.00 USD

Virtual: Online - PST
          

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