Building Streaming Data Analytics on AWS
This 1-day course is a look into streaming data analytics on AWS.
In this 1-day intermediate course, you will learn how to create streaming data analytics solutions using AWS services like Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (Amazon MSK). Amazon Kinesis is a powerful service for real-time data streaming, while Amazon MSK provides a secure and fully managed Apache Kafka service. The course will cover how these services work with other AWS tools such as AWS Glue and AWS Lambda, focusing on the key components of data analytics, including data ingestion, storage, and processing. You will also learn best practices for security, performance, and cost management when using Kinesis and Amazon MSK.
The course includes presentations, hands-on labs, discussions, and exercises. By the end of the course, you will understand the features of modern data architecture and how AWS streaming services fit into it. You will be able to design and implement a streaming data analytics solution, optimize data storage using techniques such as compression and partitioning, and select the right options for ingesting and transforming real-time data. Additionally, you will learn how to secure data, monitor analytics workloads, and apply cost management strategies.
This course is aimed at data engineers, architects, and developers interested in building real-time applications. To get the most out of this course, it is recommended that participants have at least one year of data analytics experience or experience with real-time applications, and have completed courses like Architecting on AWS or Data Analytics Fundamentals.