Cloud Computing & Virtualisation - Category Banner

Building Data Lakes on AWS

Length 1 day

Course overview

View dates &
book now

Course locations >>

Why study this course

Learn how to build an operational data lake that supports analysis of both structured and unstructured data.

You will also learn the components and functionality of the 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 analyse data. The course lectures and labs further your learning with the exploration of several common data lake architectures.

Aligns to certification

AWS Certified Data Engineer - Associate

Request Course Information

What you’ll learn

This course is designed to teach participants how to:

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, analyse, and visualise data within a data lake

AWS at Lumify Work

Lumify Work is an official AWS Training Partner for Australia, New Zealand, and the Philippines. Through our Authorised AWS Instructors, we can provide you with a learning path that’s relevant to you and your organisation, so you can get more out of the cloud. We offer virtual and face-to-face classroom-based training to help you build your cloud skills and enable you to achieve industry-recognised AWS Certification.

View all AWS courses

Who is the course for?

This course is intended for:

Data platform engineers
Solutions architects
IT professionals

Course subjects

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
Recognise 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

Recognise 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 analyse 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
Visualise data with Amazon QuickSight
Lab 3: Automate data lake creation using AWS Lake Formation blueprints
Lab 4: Data visualisation using Amazon QuickSight

Module 6: Architecture and course review

Post course knowledge check
Architecture review
Course review

Please note: This is an emerging technology course. Course outline is subject to change as needed.

Prerequisites

It is recommended that attendees have the following prerequisites:

Completed AWS Technical Essentials course
One year of experience building data analytics pipelines or have completed the Data Analytics Fundamentals digital course

Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.