Customers in the telecom industry face the challenge of learning about services offered by Amazon Web Services (AWS). They need to learn how these services apply to both communications service providers (CSPs) and products for telecom customers. They also need to know where to find examples of how to build a telecom Internet of Things (IoT) layer to service telecom business-to-business (B2B) customers.
This course will teach telecom customers and learners the concept of a data lake. They will understand the services and machines that are part of a telecom data lake. They will also understand how to bring the data together as a precursor to more advanced data analytics and telecom-specific service products.
Activities
This course includes reading material, demonstrations, videos, and resources.
Course objectives
In this course, you will learn to do the following:
   •   Understand the foundational concepts of a telecom data lake.
   •   Explain business value of connecting IoT systems and machines to a telecom data lake.
   •   Understand how to use AWS services to generate IoT insights.
   •   Understand the path to further learning and practice.
Intended audience
This course is intended for the following:
   •   Those in roles related to system architecture and business in the telecom industry.
Prerequisites
We recommend that attendees of this course have the following:
   •   Familiarity with telecom industry
   •   Familiarity with cloud computing and AWS Cloud
Course outline
Module 1: Introduction
   •   How to Use This Course
   •   Course Introduction
   •   Solution Introduction
Module 2: Underlying Technology and Architectures
   •   Introduction to Data Lakes
   •   Introduction to the Telecom Data Lake
   •   Introduction to AWS IoT Core
   •   Introduction to AWS IoT Device Defender
   •   Introduction to AWS IoT TwinMaker
   •   Introduction to AWS IoT FleetWise
   •   Connectivity with AWS IoT Greengrass
   •   High-Level Architecture
Module 3: Use Cases
   •   Use Cases
Module 4: Software Demonstration
   •   Software Demonstration
Module 5: Course Summary
   •   Additional Resources
   •   Feedback
