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Fundamentals of a Modern Data Strategy on AWS

Course content updated by LearnQuest
Price
0 USD
1.5 Hours
AWS-1015
Webinar
Amazon Web Services
Limited Time Offer
20% Off Check Point Training Courses
Promo Code: checkpoint20
Valid through October 31, 2022

AWS Training Pass

Take advantage of flexible training options with the AWS Training Pass and get Authorized AWS Training for a full year.

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Prices reflect a 22.5% discount for IBM employees.
Prices reflect the Accenture employee discount.
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Course Description

Overview

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.

We recommend that attendees of this event continue learning with these:
  • Courses
    • Big Data on AWS
    • Building Data Analytics Solutions Using Amazon Redshift
    • Building Data Lakes on AWS
    • Data Warehousing on AWS
    • Planning and Designing Databases on AWS


 

Objectives

During this event, students 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

Audience

This event is intended for:
  • Data architects, data scientists, and data analysts new to the AWS Cloud
  • Solutions architects
  • Database administrators

Prerequisites


     

Topics

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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