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Building Data Lakes on AWS

  • Length 1 day
  • Price  NZD 895 exc GST
Course overview
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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.

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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

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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

  • 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.


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.

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