IoT Data Analytics and Storage

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Enrollment in this course is by invitation only

About this course

Are you ready to help your business begin realizing the business benefits promised by the Internet of Things revolution? Do you want to discover the hidden insights waiting in your business data?

In this course, you will learn how to make the most of your live-stream and historical telemetry data that is being produced by the IoT devices and sensors that support your business.

Please Note: Learners who successfully complete this course can earn a CloudSwyft digital certificate and skill badge - these are detailed, secure and blockchain authenticated credentials that profile the knowledge and skills you’ve acquired in this course.

What You’lll Learn：

After completing this course, students will be able to:

Describe typical telemetry data produced by Azure IoT devices
Explain various strategies for analyzing IoT data
Explain the differences between warm and cold storage and how each technology is best used
Describe how Azure Data Lake can be used for cold storage
Explain the process for processing IoT data with IoT Hub, Data Lake Analytics, and Data Lake Storage
Understand strategies for querying and analyzing Azure Data Lake data sets
Identify the benefits of warm storage
Identify operational vs. archive data sets from IoT
Provision and configure Azure Cosmos DB
Integrate Azure Cosmos DB with Azure Stream Analytics
Write IoT data into Cosmos DB as Warm Storage
Query Cosmos DB for IoT data
Explain the role of IoT Edge devices in analyzing and acting on telemetry data
Describe use cases for running analytics on edge devices
Modify web-based stream analytics jobs for edge deployment
Deploy analytics jobs onto edge devices
Deploy other analytics code onto edge devices
Combine streaming data with reference data in queries
Write queries with different types of time windows
Chain together streaming analytics jobs, to allow more sophisticated inputs and outputs
Combine warm and cold storage strategies with edge analytics and strategies to quickly react to telemetry data
Describe options for performing device management tasks, based on real-time data

Course Syllabus

This course is completely lab-based. There are no lectures or required reading sections. All of the learning content that you will need is embedded directly into the labs, right where and when you need it. Introductions to tools and technologies, references to additional content, video demonstrations, and code explanations are all built into the labs.

Some assessment questions will be presented during the labs. These questions will help you to prepare for the final assessment.

The course includes four modules, each of which contains two or more lab activities. The lab outline is provided below.

Module 1: IoT Analytics and Cold Storage

Lab 1: Configuring the Wind Farm Simulator
Lab 2: Getting Started with Data Lake Storage and Analytics

Module 2: Warm Storage

Lab 1: Getting Started with Warm Storage
Lab 2: Implementing Business System Integration

Module 3: Analytics on the Edge

Lab 1: Getting Started with IoT Edge
Lab 2: Implementing Analytics on the Edge
Lab 3: Deploying an Azure Function to the IoT Edge

Module 4: Advanced Analytics

Lab 1: Constructing Analytics Queries
Lab 2: Managing Analytics Topologies
Lab 3: Device Management and Analytics

Prerequisites

Students should understand the following:

How IoT is used to achieve business goals
How to establish 2-way communication between devices (either real or simulated) and the IoT Hub.

Course Staff

Chris Howd

Engineer and Software Developer

Microsoft

Chris is an engineer and software developer who has been working at Microsoft in various roles for the past 15 years. Before coming to Microsoft, Chris worked for the U.S. Department of Defense designing and developing computer controlled instrumentation and robotic systems, and was a self-employed contractor doing engineering research with NASA and select engineering start-ups.

Rob Collins

Founder and lead consultant

RCP Consultants

Rob Collins is founder and lead consultant at RCP Consultants. He has been working with C# and the .NET Framework since its initial release more than fifteen years ago. He has been delivering software for enterprise customers, the mass market retail chain, mid-market companies, and startups for more than twenty years.