Programmer, Scientist, and IT Manager
The Netherlands, Aizonic
Bas is a programmer, scientist, and IT manager. He works as a Technology Lead in the AI and big data domain. His academic background is in Artificial Intelligence and Informatics. Bas has a background in software development, design and architecture with a broad technical view from C++ to Prolog to Scala. He occasionally teaches programming courses and is a regular speaker on conferences and informal meetings, where he brings a mixture of market context, his own vision, business cases, architecture and source code in an enthusiastic way towards his audience.
Streaming Processing – an Overview of the Concepts, Architecture and Technology of Doing Data Science on Real-Time Data
Streaming Processing (or Fast Data processing) is becoming an increasingly popular subject in financial services, marketing, the internet of things, and healthcare. A typical stream processing solution follows a ‘pipes and filters’ pattern that consists of three main steps: detecting patterns on raw event data (Complex Event Processing), evaluating the outcomes with the aid of business rules and machine learning algorithms, and deciding on the next action. At the core of this architecture is the execution of predictive models that operate on enormous amounts of never-ending data streams. In this talk, Bas will present an architecture for streaming analytics solutions that covers many use cases that follow this pattern: actionable insights, fraud detection, log parsing, traffic analysis, factory data, the IoT, and others. He’ll go through a few architecture challenges that will arise when dealing with streaming data, such as latency issues, event time vs server time, and exactly-once processing. Finally, he’ll discuss some technology options as possible implementations of the architecture.