Apache Kafka® + Machine Learning for Supply Chain

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Presented by

Kai Waehner, Confluent + Graham Ganssle, Expero

About this talk

Automating multifaceted, complex workflows requires hybrid solutions like streaming analytics of IoT data, batch analytics like machine learning solutions, and real-time visualizations. Leaders in organizations who are responsible for global supply chain planning are responsible for working with and integrating with data from disparate sources around the world. Many of these data sources output information in real-time, which assists planners in operationalizing plans and interacting with manufacturing output. IoT sensors on manufacturing equipment and inventory control systems feed real-time processing pipelines to match actual production figures against planned schedules to calculate yield efficiency.  Using information from both real-time systems and batch optimization, supply chain managers are able to economize operations and automate tedious inventory and manufacturing accounting processes. Sitting on top of all these systems is a supply chain visualization tool, enabling users' visibility over the global supply chain. If you are responsible for key data integration initiatives, join for a detailed walk through of a customer's use of this system built using Confluent and Expero tools.  WHAT YOU'LL LEARN:  •See different use cases in automation industry and Industrial IoT (IIoT) where an event streaming platform adds business value.  •Understand different architecture options to leverage Apache Kafka and Confluent. •How to leverage different analytics tools and machine learning frameworks in a flexible and scalable way. •How real-time visualization ties together streaming and batch analytics for business users, interpreters, and analysts. •Understand how streaming and batch analytics optimize the supply chain planning workflow. •Conceptualize the intersection between resource utilization and manufacturing assets with long term planning and supply chain optimization.
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