Build real-time analytics for a ride-sharing app (ANT401)

· 102 words · 1 minute read

In this session, we walk through how to perform real-time analytics on ride-sharing and taxi data, and we explore how to build a reliable, scalable, and highly available streaming architecture based on managed services. You learn how to deploy, operate, and scale an Apache Flink application with Amazon Kinesis Data Analytics for Java applications. Leave this workshop knowing how to build an end-to-end streaming analytics pipeline, starting with ingesting data into a Kinesis data stream, writing and deploying a Flink application to perform basic stream transformations and aggregations, and persisting the results to Amazon Elasticsearch Service to be visualized from Kibana.