CloudAcademy

Getting Started with Amazon Redshift

The hands-on lab is part of this learning path

Big Data – Specialty Certification Preparation for AWS
course-steps 14 lab-steps 5 quiz-steps 3

Lab Steps

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Logging in to the Amazon Web Services Console
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Creating the Redshift Cluster
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Connecting to the Virtual Machine using SSH
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Retrieving the Redshift IAM role
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Loading data into Redshift
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Running sample queries
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Resizing the cluster
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Cleaning up the environment

Ready for the real environment experience?

DifficultyBeginner
Duration1h 30m
Students411

Description

Lab Overview

Amazon Redshift is a managed data warehouse that allows you to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools. Redshift uses query optimization, columnar storage, parallel execution, and high performance disks to query petabytes of data in seconds. In this Lab, you will learn how to create, query, and resize a Redshift cluster.

Lab Objectives

Upon completion of this lab you will be able to:

  • Log in to the AWS Management Console

  • Connect to an EC2 instance to communicate with Redshift

  • Create and resize a Redshift cluster

  • Load data into Redshift

  • Query data within Redshift

Lab Prerequisites

You should be familiar with:

  • Basic understanding of local operating system and computer use

  • Secure terminal connection software such as Terminal (macOS) or PuTTY (Windows)

Lab Environment

Before completing the lab instructions the environment will look as follows:

After completing the lab instructions the environment should look similar to:

Updates

November 21st, 2018 - Updated Lab to use the new default dc2.large instance type and modified the Lab permission policy to allow resizing the cluster to account for IAM changes in Redshift

About the Author

Eric is a Lab Researcher and Developer working to add to Cloud Academy's library of hands-on labs. He is an IT veteran who enjoys the ever-changing landscape of cloud computing. He also relishes live classical music performances, because sometimes engineering is better heard than seen.