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AWS DISCOVERY DAY: FUNDAMENTALS OF A MODERN DATA STRATEGY ON AWS

  • Course Code GKAWS-MDS
  • Duration 1 day

Course Delivery

Public Classroom Price

Free of Charge

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Course Delivery

This course is available in the following formats:

  • Public Classroom

    Traditional Classroom Learning

  • Virtual Learning

    Learning that is virtual

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Course Overview

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Learn how to modernize, unify, and innovate your way to a modern data strategy with AWS.

Organizations need a data strategy to succeed, but there’s no one-size fits all approach. Every organization will have unique objectives and obstacles. Join this event to learn how to modernize, unify, and innovate your way to a modern data strategy with AWS.

- Level: Fundamental
- Duration: 1.5 hours

Course Schedule

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    • Delivery Format: Virtual Learning
    • Date: 06 June, 2025
    • Location: Virtual

    Free of Charge

    • Delivery Format: Virtual Learning
    • Date: 05 September, 2025
    • Location: Virtual

    Free of Charge

    • Delivery Format: Virtual Learning
    • Date: 05 December, 2025
    • Location: Virtual

    Free of Charge

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Target Audience

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This event is intended for:

- Data architects, data scientists, and data analysts new to the AWS Cloud
- Solutions architects
- Database administrators

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Course Objectives

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During this event, you will learn:

  • How AWS services help you modernize, unify, and innovate your data infrastructure
  • How to use AWS services to provide secure and well-governed access to data
  • How to innovate with AI/ML by harnessing your data with built-in ML
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Course Content

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Section 1: Introduction

  • Business value of a modern data strategy
  • Challenges
  • Use cases
  • Traditional vs. cloud
  • Modern data strategy on AWS

Section 2: Modernize

  • Relational databases
  • Purpose-built databases

Section 3: Unify

  • Data lakes with Amazon S3
  • Lake house approach on AWS
  • Purpose-built data services
  • Breaking down data silos
  • Unified governance

Section 4: Innovate

  • Machine learning (ML) services
  • Artificial intelligence (AI) services
  • Data stores, data lakes, and BI tools with built-in ML

Section 5: Next steps

  • Resources to continue learning
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