Big Data on AWS

3 Labs · 40 Credits · 3h 40m

Use Case (Experienced) 9 big data on aws option 02

This quest is designed to teach you how to work with AWS services to perform big data analytics on the cloud.

Working with Amazon Redshift

The lab demonstrates how to use Amazon RedShift to create a cluster, load data, run queries and monitor performance. Note: Students will download a free SQL client as part of this lab.

Icon  advanced advanced 10 Credits 45 Minutes

Exploring Google Ngrams with Amazon EMR

This lab demonstrates how to launch an Amazon Elastic MapReduce (EMR) cluster for Big Data processing and use Hive with SQL-style queries to analyze data. You will create a Hadoop cluster using Amazon EMR which will allow to run interactive Hive queries against data stored in Amazon S3. You will use Hive to normalize the data in a more useful way, and you will run queries to analyze the data.

Icon  expert expert 15 Credits 1 Hour

Advanced Amazon Redshift: Analytics and Amazon Machine Learning

In this lab, you will build a smart solution using Amazon Redshift and Amazon Machine Learning that predicts delays for flights originating in Chicago’s O’Hare international airport. You will learn how to analyze large amounts of data using Redshift. Then you will practice using Machine Learning to create a model that will predict flight delays. Prerequisites: To successfully complete this lab, you should be familiar with Redshift concepts by taking the introductory lab at Some knowledge of SQL and Python programming is required, although full solution code is provided. You should be comfortable using RDP to connect to a Windows server and using SQL client software. You should have at a minimum taken the “Introduction to Amazon Redshift” and “Introduction to Machine Learning” labs at Note: this lab must run (currently) in us-east-1 for the Machine Learning service. Be sure to check in the AWS console that you are running in us-east-1 (N. Virginia) and change to us-east-1 if necessary.

Icon  expert expert 15 Credits 1 Hour 45 Minutes