Building Data Lakes on AWS Duration: 1 Day

Course details

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

Module 3: Building a Data Lake with AWS Lake Formation
• 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
• Lab 01: Building a Data Lake with AWS Lake Formation

Module 4: Data Processing and Analysis
• 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
• Explain the available built-in Blueprints to create and populate a new Lake Formation
• Describe methods for applying advanced permissions to secure data access and workflow.
• Describe fine-grained row/cell access control
• Explain the Lake Formation Tag-based access control mechanism and the different use
cases for Named access control vs. Tag-based access control
• Describe access flow that enforces fine-grained access policies to both catalog metadata
and underlying data resource for analytics services connecting to Lake Formation

Module 6: Modern Data Architecture
• Explain capabilities of a modern data architecture: Scalable data lakes, Purpose-build
analytics services, Seamless data movement, unified governance, and performance and
cost-effectiveness
• Articulate the typical data movement within a modern data architecture: Inside out,
Outside in, Around the perimeter, and Sharing across.
• Describe focus of building and maintaining data products as a service.
• Describe a typical Data Mesh architecture using Lake Formation and the key enablers
supporting this methodology
• Lab 3: Building and publishing a data product in Lake Formation

Module 7: Course Wrap Up
• Post course knowledge check
• Architecture review
• Course review