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Building Streaming Data Analytics Solutions on AWS

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Last Update:

October 7, 2025

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Course Overview

In this course, you will learn to build streaming data analytics solutions using AWS services, including Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (Amazon MSK). Amazon Kinesis is a massively scalable and durable real-time data streaming service. Amazon MSK offers a secure, fully managed, and highly available Apache Kafka service. You will learn how Amazon Kinesis and Amazon MSK integrate with AWS services such as AWS Glue and AWS Lambda. The course addresses the streaming data ingestion, stream storage, and stream processing components of the data analytics pipeline. You will also learn to apply security, performance, and cost management best practices to the operation of Kinesis and Amazon MSK.

Course Objectives

In this course, you will learn to:

Understand the features and benefits of a modern data architecture. Learn how AWS streaming services fit into a modern data architecture.
Design and implement a streaming data analytics solution
Identify and apply appropriate techniques, such as compression, sharding, and partitioning, to optimize data storage
Select and deploy appropriate options to ingest, transform, and store real-time and near real-time data
Choose the appropriate streams, clusters, topics, scaling approach, and network topology for a particular business use case
Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights
Secure streaming data at rest and in transit
Monitor analytics workloads to identify and remediate problems
Apply cost management best practices

Methodology

This course includes presentations, practice labs, discussions, and class exercises.

Target Audience

This course is intended for:

Data engineers and architects
Developers who want to build and manage real-time applications and streaming data analytics solutions

Prerequisites

We recommend that attendees of this course have:

At least one year of data analytics experience or direct experience building real-time applications or streaming analytics solutions. We suggest the Streaming Data Solutions on AWS whitepaper for those that need a refresher on streaming concepts.
Completed either Architecting on AWS or Data Analytics Fundamentals
Completed Building Data Lakes on AWS

Module A : Overview of Data Analytics and the Data Pipeline

Data analytics use cases
Using the data pipeline for analytics

Module 1 : Using Streaming Services in the Data Analytics Pipeline

The importance of streaming data analytics
The streaming data analytics pipeline
Streaming concepts

Module 2 : Introduction to AWS Streaming Services

Streaming data services in AWS
Amazon Kinesis in analytics solutions
Demonstration: Explore Amazon Kinesis Data Streams
Practice Lab: Setting up a streaming delivery pipeline with Amazon Kinesis
Using Amazon Kinesis Data Analytics
Introduction to Amazon MSK
Overview of Spark Streaming

Module 3 : Using Amazon Kinesis for Real-time Data Analytics

Exploring Amazon Kinesis using a clickstream workload
Creating Kinesis data and delivery streams
Demonstration: Understanding producers and consumers
Building stream producers
Building stream consumers
Building and deploying Flink applications in Kinesis Data Analytics
Demonstration: Explore Zeppelin notebooks for Kinesis Data Analytics
Practice Lab: Streaming analytics with Amazon Kinesis Data Analytics and Apache Flink