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December 5-6, 2016: Training
December 6–8, 2016: Tutorials & Conference

A simplified enterprise architecture for real-time stream processing

Mathieu Dumoulin (MapR Technologies)
1:45pm–2:25pm Thursday, December 8, 2016
IoT and intelligent real-time applications
Location: 323 Level: Non-technical
Average rating: ***..
(3.75, 4 ratings)

Prerequisite Knowledge

  • A basic understanding of enterprise IT

What you'll learn

  • Learn about stream processing and its use cases for enterprise IT
  • Explore a realistic example of how stream processing can be implemented with existing Java Enterprise skills that are well understood and accepted in most large enterprises
  • Understand why stream processing is useful for production use cases right now, not just a speculative technology of the future


Many talks at Strata focus on big data analytics, and with good reason. But we rarely get to hear about business logic-focused enterprise applications, despite the fact that it was an estimated $150B market in 2015 according to Gartner.

Mathieu Dumoulin shares a use case that details a modern, enterprise-friendly, and easy-to-develop architecture for streaming processing. Mathieu begins with an explanation and rationale for streaming processing before presenting an architecture based on JBoss Drools and large-scale streaming using the Kafka API. The main benefits of this architecture are a clear separation of business rules creation and editing from custom enterprise application development requiring minimal expertise in complex Hadoop ecosystem engineering. Mathieu then illustrates this architecture by exploring a successful production use case for Busan, South Korea’s Smart City initiative, backed by a working, live demo with a real-time Kibana dashboard showing exactly what’s going on. You’ll learn how easy it is for business users to create and edit business rules using a web application GUI.

Topics include:

  • An introduction to real-time stream processing
  • Use cases, benefits, and implementation challenges
  • An overview of the proposed real-time stream processing architecture
  • Key benefits of the proposed architecture
  • The smart city traffic management use case
  • A live demo of the smart city traffic management use case
Photo of Mathieu Dumoulin

Mathieu Dumoulin

MapR Technologies

Mathieu Dumoulin is a data scientist in MapR Technologies’s Tokyo office, where he combines his passion for machine learning and big data with the Hadoop ecosystem. Mathieu started using Hadoop from the deep end, building a full unstructured data classification prototype for Fujitsu Canada’s Innovation Labs, a project that eventually earned him the 2013 Young Innovator award from the Natural Sciences and Engineering Research Council of Canada. Afterward, he moved to Tokyo with his family, where he worked as a search engineer at a startup and a managing data scientist for a large Japanese HR company, before coming to MapR.