In this talk, we would like to present a streaming analytics platform that we are building at ING with Scala, Flink, and Kafka to empower the thousands of employees of ING to compute and facilitate insights (in real-time) that is relevant, personal and actionable to our millions of customers. We use this platform for use cases such as fraud detection, personalization and plan is to transform ING from batch-oriented towards real-time. At the very core of the platform, we have a linguistic abstraction (an external DSL) by which business users can specify how to transform the raw-events from the Event Bus to relevant events, extract relevant features and score ML/rule-based models. Hence, without any intervention from engineers, they can quickly develop programs with the programming model, deploy them, and see the result in action. In essence, it showcases how language engineering can assist and empower non-technical resources in a large organization such as ING in solving complex problems and add business values without requiring any assistance of the technical experts.
Adil Akhter is a functional programmer, and a Lead Data Engineer at ING where he is involved in building a state-of-the-art streaming analytics platform with Scala, Flink, Akka, etc. He is passionate about building resilient and fault-tolerant distributed systems with the applications of different formalism (such as, π-calculus, category theory). In his spare time, he hacks with Haskell and Idris, organise different meetups and speaks at conferences.