Stream Processing v.1.0

Join Data Natives and Quix for an evening all about streaming data. We’ll have food, drinks, three engaging talks and plenty of opportunities to chat about fast data, machine learning and real-time analytics!

Event Schedule:

6:00-6:15: Registration and networking

6:15: 6:20: Intro speak by Data Natives!

6:20-6:45: Lukas Bachus - Big Data Solution Architect at it-novum GmbH

Why real-time analytics is possible and necessary today

In this presentation, Lukas Bachus will present why real-time analytics is possible and necessary today, illustrated with a series of compelling business cases. Lukas will then outline a roadmap to transform your own legacy analytics landscape into stream processing as well as the technology stack that enables this paradigm shift.

6:50-7:15: Timo Walther, software engineer and lead of the SQL team at Ververica

Streaming Analytics with Apache Flink
What do Uber, Netflix, TikTok and other digital leaders have in common? They provide a superior customer experience enabled by data driven real-time business decisions at scale. For years, Apache Flink has been at the heart of this development powering use cases at the intersection of real-time analytics and event-driven applications.

In this demo-heavy talk, I will briefly introduce Apache Flink and then focus on its analytical interfaces. Afterwards you’ll have an impression of what it means to develop analytical applications with Apache Flink and understand our flavour of unified analytics.

7:20-7:40: Tomas Neubauer, co-founder and CTO at Quix, Javier Blanco Cordero, senior data scientist at Quix

Live build of a Python service that tracks, transforms and delivers heart rate data in real time using open source components

This presentation offers developers, data engineers and data scientists the opportunity to learn about streaming data, real-time analytics and real-time visualization. We’ll build a python service that collects data from a heart rate monitor, transforms it in streams, and sends alerts to a phone when the wearer’s heart rate spikes above a set point. We’ll show how to include complex transformations to the data, such as how to calculate calories burned with Python. We'll use Quix, Twilio, and open source components that connect, transform and deliver data in real time to build the application from scratch in front of the audience. This stack means you can handle data on your own, with no IT or data support needed.

7:45-9:00 food, drinks and networking :)

The skills applied in this project can be applied to use cases in fields such as finance, mobility and energy, which require easy access to current information. Whether you’ve been processing data on a message broker like Kafka for a while, or you’re simply stream-curious, you’re welcome to join the conversation.

This event applies 3G rules for visitors.
We look forward to meeting you in Berlin!

#streamprocessing #Kafka #ApacheFlink #ML #AI