Module 1: Introduction to data lakes
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Describe the value of data lakes
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Compare data lakes and data warehouses
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Describe the components of a data lake
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Recognize common architectures built on data lakes
Module 2: Data ingestion, cataloging, and preparation
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Describe the relationship between data lake storage and data ingestion
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Describe AWS Glue crawlers and how they are used to create a data catalog
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Identify data formatting, partitioning, and compression for efficient storage and query
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Lab 1: Set up a simple data lake
Module 3: Data processing and analytics
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Recognize how data processing applies to a data lake
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Use AWS Glue to process data within a data lake
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Describe how to use Amazon Athena to analyze data in a data lake
Module 4: Building a data lake with AWS Lake Formation
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Describe the features and benefits of AWS Lake Formation
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Use AWS Lake Formation to create a data lake
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Understand the AWS Lake Formation security model
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Lab 2: Build a data lake using AWS Lake Formation
Module 5: Additional Lake Formation configurations
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Automate AWS Lake Formation using blueprints and workflows
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Apply security and access controls to AWS Lake Formation
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Match records with AWS Lake Formation FindMatches
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Visualize data with Amazon QuickSight
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Lab 3: Automate data lake creation using AWS Lake Formation blueprints
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Lab 4: Data visualization using Amazon QuickSight
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Building Data Lakes on AWS
Module 6: Architecture and course review
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Post course knowledge check
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Architecture review
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Course review
Get the course outline PDF >>