From application monitoring to fraud detection to feedback loops for IoT devices, streaming applications solve wide range of business use cases. Data from hundreds of thousands of connected devices needs to be collected, processed and analyzed in real-time so that businesses can react swiftly to new information and take timely decisions or insights.
AWS Data Streaming & Analytics services offers fully managed and scalable services that allows you to rapidly build real-time streaming analytics use cases. In this workshop, you will learn how to use those services to collect streaming data, process them in real-time, gain insights real-time and durably store the data in data lakes for further downstream analytics.
Overview of Real-time streaming use cases
- Characteristics of real-time data streaming applications
- Challenges in collecting and processing streaming data
- How streaming data integrates with data lakes?
- Introduction to Amazon Kinesis Platform
Module 1: Deep Dive into Amazon Kinesis Data Streams
- Key concepts of Amazon Kinesis Data Streams
- Ways of ingesting streaming data into Kinesis Data Streams
- How to process data from Kinesis Data Streams in real-time
- Integrations with open source libraries and tool kits
- Best practices for scaling and performance
Lab 1: Build a real-time leaderboard for a mobile gaming app
Module 2: Streaming data delivery using Amazon Kinesis Data Firehose
- Overview of Amazon Kinesis Data Firehose
- Ways of ingesting streaming data into Kinesis Data Firehose
- Kinesis Data Firehose data delivery destinations
- Data transformations before delivery to destinations
- Best practices for performance
Lab 2: Deliver streaming data from a music app to your data lake for analytics
Module 3: Streaming analytics using Amazon Kinesis Data Analytics
- Key concepts of Amazon Kinesis Data Analytics
- Understanding of Windowed Queries
- Inputs and Outputs for Kinesis Data Analytics
- Ways of running streaming analytics
Lab 3: Run continuous processing queries on streaming data using Kinesis Data Analytics
Course Wrap up
- Course Summary
- Quiz
- Next steps and further resources
