Module 1: Introduction to data lakes

• • Describe the value of data lakes
• • Compare data lakes and data warehouses
• • Describe the components of a data lake
• • Recognize common architectures built on data lakes

Module 2: Data ingestion, cataloging, and preparation

• • Describe the relationship between data lake storage and data ingestion
• • Describe AWS Glue crawlers and how they are used to create a data catalog
• • Identify data formatting, partitioning, and compression for efficient storage and query
• • Lab 1: Set up a simple data lake

Module 3: Data processing and analytics

• • Recognize how data processing applies to a data lake
• • Use AWS Glue to process data within a data lake
• • Describe how to use Amazon Athena to analyze data in a data lake

Module 4: Building a data lake with AWS Lake Formation

• • Describe the features and benefits of AWS Lake Formation
• • Use AWS Lake Formation to create a data lake
• • Understand the AWS Lake Formation security model
• • Lab 2: Build a data lake using AWS Lake Formation

Module 5: Additional Lake Formation configurations

• • Automate AWS Lake Formation using blueprints and workflows
• • Apply security and access controls to AWS Lake Formation
• • Match records with AWS Lake Formation FindMatches
• • Visualize data with Amazon QuickSight
• • Lab 3: Automate data lake creation using AWS Lake Formation blueprints
• • Lab 4: Data visualization using Amazon QuickSight

Module 6: Architecture and course review

• • Post course knowledge check
• • Architecture review
• • Course review