Module 1: Overview of Big Data 

• What is big data
• The big data pipeline
• Big data architectural principals

Module 2: Big Data ingestion and transfer 

• Overview: Data ingestion
• Transferring data

Module 3: Big data streaming and Amazon Kinesis 

• Stream processing of big data
• Amazon Kinesis
• Amazon Kinesis Data Firehose
• Amazon Kinesis Video Streams
• Amazon Kinesis Data Analytics

Module 4: Big data storage solutions 

• AWS data storage options
• Storage solutions concepts
• Factors in choosing a data store

Module 5: Big data processing and analytics 

• Big data processing and analytics
• Amazon Athena

Module 6: Apache Hadoop and Amazon EMR 

• Introduction to Amazon EMR and Apache Hadoop
• Best practices for ingesting data
• Amazon EMR
• Amazon EMR architecture

Module 7: Using Amazon EMR 

• Developing and running your application
• Launching your cluster
• Handling output from your completed jobs

Module 8: Hadoop programming frameworks 

• Hadoop frameworks
• Other frameworks for use on Amazon EMR

Module 9: Web interfaces on Amazon EMR 

• Hue on Amazon EMR
• Monitoring your cluster

Module 10: Apache Spark on Amazon EMR 

• Apache Spark
• Using Spark

Module 11: Using AWS Glue to automate ETL workloads 

• What is AWS Glue?
• AWS Glue: Job orchestration

Module 12: Amazon Redshift and big data 

• Data warehouses vs. traditional databases
• Amazon Redshift
• Amazon Redshift architecture

Module 13: Securing your Amazon deployments 

• Securing your Amazon deployments
• Amazon EMR security overview
• AWS Identity and Access Management (IAM) overview
• Securing data
• Amazon Kinesis security overview
• Amazon DynamoDB security overview
• Amazon Redshift security overview

Module 14: Managing big data costs 

• Total cost considerations for Amazon EMR
• Amazon EC2 pricing models
• Amazon Kinesis pricing models
• Cost considerations for Amazon DynamoDB
• Cost considerations and pricing models for Amazon Redshift
• Optimizing cost with AWS

Module 15: Visualizing and orchestrating big data 

• Visualizing big data
• Amazon QuickSight
• Orchestrating a big data workflow

Module 16: Big data design patterns 

• Common architectures

Module 17: Course wrap-up 

• What’s next?