Course Overview

In Building Data Lakes on AWS training you will use AWS Lake Formation to build a data lake, AWS Glue to build a data catalog, and Amazon Athena to analyze data. The course lectures and labs further your learning with the exploration of several common data lake.

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Level: Intermediate

Duration: 1 Day

Delivery Type: Instructor-Led Training

Course Objectives

• Apply data lake methodologies in planning and designing a data lake
• Articulate the components and services required for building an AWS data lake
• Secure a data lake with appropriate permission
• Ingest, store, and transform data in a data lake
• Query, analyze, and visualize data within a data lake

Who Should Go For This Training?

• Data Platform Engineers
• Solutions Architects
• IT Professionals

Prerequisites

*Required

• One year of experience building data analytics pipelines
• AWS Technical Essentials

Course Outline

Day 1:

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