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Applying ML on your Data in Motion with AWS and Confluent

Event-driven application architectures are becoming increasingly common as a large number of users demand more interactive, real-time, and intelligent responses. Yet it can be challenging to decide how to capture and perform real-time data analysis and deliver differentiating experiences. Join experts from Confluent and AWS to learn how to build Apache Kafka®-based streaming applications backed by machine learning models. Adopting the recommendations will help you establish repeatable patterns for high performing event-based apps.

Présentateurs

Joseph Morais

Joseph Morais started early in his career as a network/solution engineer working for FMC Corporation and then Urban Outfitters (UO). At UO, Joseph joined the e-commerce operations team, focusing on agile methodology, CI/CD, containerization, public cloud architecture, and infrastructure as code. This led to a greenfield AWS opportunity working for a startup, Amino Payments, where he worked heavily with Kafka, Apache Hadoop, NGINX, and automation. Before joining Confluent, Joseph helped AWS enterprise customers scale through their cloud journey as a senior technical account manager. At Confluent, Joseph serves as cloud partner solutions architect and AWS evangelist.

Kanchan Waikar