Live-Online: Building Data Lakes on AWS: Innovative Strategies for Data Integration and Analysis on AWS

In this course, you will learn the components and functionality of AWS services involved in creating a data lake. You will use AWS Lake Formation to build a data lake, AWS Glue to build a data catalog, and Amazon Athena to analyze data. Lectures and labs enhance your learning by exploring several common data lake architectures.

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: 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: 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: Automate data lake creation using AWS Lake Formation blueprints
• Lab: Data visualization using Amazon QuickSight

Module 6: Architecture and course review

• Post course knowledge check
• Architecture review
• Course review

• Applying data lake methodologies in planning and designing a data lake
• Articulating the components and services required for building an AWS data lake
• Securing a data lake with appropriate permission
• Ingesting, storing, and transforming data in a data lake
• Querying, analyzing, and visualizing data within a data lake

This course prepares you for AWS Data Analytics certification, among other courses of the AWS Data Analytics job role track.

This course is intended for the following job roles:

• Data Analytics
• Machine Learning & AI

We recommend that attendees of this course:

• have basic knowledge on data analytics fundamentals
• have initial experience in architecting data solutions on AWS