Cloud Computing and Virtualisation

Building Data Lakes on AWS

  • Length 1 day
  • Price  $950 inc GST
Course overview
View dates &
book now
Register interest

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.

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

  • Plan and design a data lake using established data lake methodologies

  • Describe the components and services required for building a data lake on AWS

  • Explain how to secure a data lake on AWS using appropriate permissions

  • Compare the ways data can be ingested, stored, and transformed in a data lake on AWS

  • Analyse and visualise data stored in a data lake on AWS

  • Build and automate deployment of a data lake on AWS

  • Describe the role of a data lake within a modern data architectur


AWS Partner Logo - Advanced Tier

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.


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

Module 3: Building a Data Lake with AWS Lake Formation

  • 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

  • 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-built 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

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:


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.


Request Course Information

Awaiting course schedule

If you would like to receive a notification when this course becomes available, enter your details below.

Personalise your schedule with Lumify USchedule

Interested in a course that we have not yet scheduled? Get in touch, and ask for your preferred date and time. We can work together to make it happen.