Workshop: Analytics on AWS

Contributors:

• Vikas Omer | Amazon Web Services | Linkedin
• Aneesh Chandra PN | Amazon Web Services | Linkedin

Lab Architecture

Learning outcomes from this workshop?

• Design serverless data lake architecture
• Build a data processing pipeline and Data Lake using Amazon S3 for storing data
• Use Amazon Kinesis for real-time streaming data
• Use AWS Glue to automatically catalog datasets
• Run interactive ETL scripts in an Amazon SageMaker Jupyter notebook connected to an AWS Glue development endpoint
• Use EMR to run a Spark transformation job
• Load data to Amazon Redshift from Glue
• Intro into Amazon Redshift Best design practices.
• Query data using Amazon Athena & visualize it using Amazon QuickSight

Pre-requisites:

• You need to have access to an AWS account with AdminstratorAccess
• This lab should be executed in us-east-1 region
• Best is to follow links from this guide & open them in new a tab
• Run this lab in a modern browser

Modules

Module	Link
Ingest and Store	link
Catalog Data	link
Transform Data with AWS Glue	link
Transform Data with EMR	link
Analyze with Athena	link
Visualize with Quicksight	link
Lambda	link
Redshift	link
Cleanup	link

Please do check on the pre-requisites for each module before starting the activities within the module.

Also, do not forget to clean up the resources at the end of the workshop!

Build on!