Course Overview
Building Streaming Data Analytics Solutions on AWS is an intermediate-level course focused on designing and implementing streaming data analytics solutions using Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (Amazon MSK). The course covers streaming data ingestion, storage, processing, security, monitoring, performance optimization, and cost management.
Participants learn how Kinesis and Amazon MSK integrate with AWS services such as AWS Glue and AWS Lambda, along with Apache Flink for stream processing. The course also covers the selection of appropriate streams, clusters, topics, scaling approaches, and network topologies for streaming analytics use cases. The course includes presentations, demonstrations, practice labs, discussions, and class exercises.
Course Objective
- Understand the features and benefits of modern data architectures and the role of AWS streaming services within them
- Design and implement streaming data analytics solutions
- Apply compression, sharding, and partitioning techniques to optimize data storage
- Select and deploy appropriate options for ingesting, transforming, and storing real-time and near-real-time data
- Choose appropriate streams, clusters, topics, scaling approaches, and network topologies for business use cases
- Understand how data storage and processing affect analysis and visualization requirements
- Secure streaming data at rest and in transit
- Monitor analytics workloads and identify and remediate performance or operational problems
- Apply cost management best practices to Amazon Kinesis and Amazon MSK
Pre-requisites
- At least one year of data analytics experience or direct experience building real-time applications or streaming analytics solutions
- Familiarity with streaming concepts is recommended for learners who need a refresher
- Completed either Architecting on AWS or Data Analytics Fundamentals
- Completed Building Data Lakes on AWS
Course Curriculum
