How to Build On Time Series Data with Apache Kafka® and Quix

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Agenda (time below is GMT):
6:00pm-6:05pm: Online networking (optional)

6:05pm-6:50pm: How to Build On Time Series Data with Apache Kafka® and Quix, explained with Formula 1 Data, Tomas Neubauer, Co-Founder and CTO at Quix

6:50pm-7:00pm: Q&A

Speaker:
Tomas Neubauer, Co-Founder and CTO at Quix

Title:
How to Build On Time Series Data with Apache Kafka® and Quix, explained with Formula 1 Data

Abstract:
This demo shows how to process and deliver time series data from Formula 1 vehicles, with Confluent and Quix at the center of a tech stack. It’s a seamless integration, as the Quix workflow lets you choose Confluent Cloud as the broker while setting up a project. Use the open source transformations and destinations, along with Jupyter Notebooks and pandas to automate a rolling average of speed and RPM that updates at the end of each window. It’s a first step into the world of time series data, especially for Python developers. It's never been easier to use Apache Kafka® for time series data.

Bio
Tomas Neubauer is a co-founder and the CTO at Quix, works as a technical authority for the engineering team and is responsible for the direction of the company across the full technical stack. He was previously technical lead at McLaren, where he led architecture uplift for Formula 1 racing real-time telemetry acquisition. He later led platform development outside motorsport, reusing the know-how he gained from racing.

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