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This course is part of a collection called 'Building Modern Data Analytics Solutions on AWS', which consists of 4 courses. You have the option to book any of the individual courses separately. If you prefer to attend all 4 courses, you can book the combined course called Building Modern Data Analytics Solutions on AWS.

Overview

In this course, you will learn how to build an operational data lake that supports analysis of both structured and unstructured data. You will 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 analyze data. The course lectures and labs further your learning with the exploration of several common data lake architectures.

Activities

This course includes presentations, lecture, hands-on labs, and group exercises.

Intended audience

This course is intended for:

  • Data platform engineers
  • Solutions architects
  • IT professionals

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Prerequisites

We recommend that attendees of this course have:

  • Completed the AWS Technical Essentials classroom course
  • One year of experience building data analytics pipelines or have completed the Data Analytics
  • Fundamentals digital courseBuilding Data Lakes on AWS
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Delegates will learn how to

In this course, you will learn 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, analyze, and visualize data within a data lake
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Course Outline

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 QuickSightBuilding Data Lakes on AWS

Module 6: Architecture and course review

  • Post course knowledge check
  • Architecture review
  • Course review

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Why choose QA

Special Notices

Please note: Effective 15th August 2022 the labs for all AWS courses will be delivered through AWS Builder labs. In order to access these labs you will need to have an Amazon account (used for Amazon.com/.co.uk retail). You can choose to use your existing Amazon account or you can elect to set up a new account utilising a new email address (such as Hotmail, Gmail, Yahoo etc etc). You can set up your new Amazon account here.

Please ensure that you have set up this Amazon account set up in advance of attending your class. Your Amazon account credentials will be used to access the AWS Builder lab environment that you will utilise during your course.

In order to access your digital course materials you are required to set up a Gilmore account in advance of attending your course. To do this please follow this link.

Dates & Locations

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