Building Streaming Data Analytics Solutions on AWS

This course provides hands-on training for designing and building streaming data analytics solutions on AWS using Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (Amazon MSK). Participants learn how to ingest, process, store, and analyze real-time and near real-time data as part of a modern data analytics pipeline. The course covers integration with services such as AWS Glue, AWS Lambda, and Kinesis Data Analytics, and emphasizes best practices for security, scalability, performance, and cost optimization. By the end of the course, learners will be able to design and operate robust streaming analytics architectures that deliver actionable business insights in real time.

• Explain the role of streaming services in modern data architectures
• Design and implement streaming data analytics pipelines on AWS
• Use Amazon Kinesis for real-time data ingestion, processing, and delivery
• Build producers, consumers, and stream processing applications using Apache Flink
• Design and manage streaming solutions using Amazon MSK and Apache Kafka
• Select appropriate streams, topics, clusters, scaling strategies, and network configurations
• Apply optimization techniques such as partitioning, sharding, and compression
• Secure streaming data at rest and in transit
• Monitor and troubleshoot streaming workloads using AWS monitoring tools
• Apply cost management and performance best practices for streaming analytics systems

• Data Engineers and Data Architects
• Developers building real-time applications
• Technical professionals responsible for streaming data analytics solutions
• Engineers working with event-driven or real-time data pipelines

• At least one year of experience with data analytics or real-time application development
• Completion of Architecting on AWS or Data Analytics Fundamentals
• Completion of Building Data Lakes on AWS or equivalent experience