Mastering Real-Time Anomaly Detection & Data Engineering

IMPORTANT PLEASE RSVP @ https://lu.ma/nza6i4bf

​We are thrilled to host the inaugural DET Warsaw Meetup! Join us at Netflix's Warsaw office (in the Wola district) for an evening of learning, networking, and fun. Refreshments will be provided.

Agenda

• ​​5:30 to 6:00 PM: Doors open, check in, and networking

• ​​6:00 to 7:00 PM: Talks and Q&A

• ​​7:00 to 8:00 PM: Closing remarks and networking

​Speakers & Talks
​Talk #1: Content and Infrastructure Data Engineering at Netflix
​Speakers: Inna Giguere (Director of Content Data Products at Netflix) and Vivek Pasari (Manager of Security and Platform Data Engineering at Netflix)

​In this talk, you will learn about how Netflix data engineering teams data products to enable content and infrastructure.
​Netflix is hiring data engineers in Warsaw! Check out open positions here.

​Talk #2: Mastering Real-Time Anomaly Detection
​Speaker: Olena Kutsenko (Staff Developer Advocate at Confluent)

​Detecting problems as they happen is essential in today’s fast-moving, data-driven world. In this talk, you’ll learn how to build a flexible, real-time anomaly detection pipeline using Apache Kafka and Apache Flink, backed by statistical and machine learning models.
​We’ll start by demystifying what "anomaly" really means - exploring the different types (point, contextual, and collective anomalies) and the difference between unintentional issues and intentional outliers like fraud or abuse.

​Then, we’ll look at how anomaly detection is solved in practice: from classical statistical models like ARIMA to deep learning models like LSTM. You’ll learn how ARIMA breaks time series into AutoRegressive, Integrated, and Moving Average components - no math degree required (just a Python library, hehe)! We’ll also uncover why forgetting is a feature, not a bug, when it comes to LSTMs, and how these models learn to detect complex patterns over time.

​Throughout, we’ll show how Kafka handles high-throughput streaming data and how Flink enables low-latency, stateful processing to catch issues as they emerge. You’ll leave knowing not just how these systems work, but when to use each type of model depending on your data and goals.

​Whether you're monitoring system health, tracking IoT devices, or looking for fraud in transactions, this talk will give you the foundations and tools to detect the unexpected - before it becomes a problem.

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If you are interested in speaking or hosting a meetup, please email community@confluent.io