The industrial environment offers a lot of interesting use cases for data enthusiasts. There are myriads of interesting challenges that can be solved by data scientists. However, collecting industrial data in general and industrial IoT (IIoT) data in particular, is cumbersome and not really appealing for anyone who just wants to work with data. Apache StreamPipes addresses this pitfall and allows anyone to extract data from IIoT data sources without messing around with (old-fashioned) protocols. In addition, StreamPipes newly developed Python client now gives Pythonistas the ability to programmatically access and work with them in a Pythonic way.

This talk will provide a basic introduction into the functionality of Apache StreamPipes itself, followed by a deeper discussion of the Python client. Finally, a live demo will show how IIoT data can be easily derived in Python and used directly for visualization and ML model training.

Tim Bossenmaier

Affiliation: inovex GmbH

Tim Bossenmaier works as a Data Engineer at inovex. There he develops and builds modern data infrastructures in customer projects, from streaming ETL pipelines to data catalogs. He is also a developer and member of the project management committee of Apache StreamPipes, an open source solution for IoT data analysis.

visit the speaker at: Github

Sven Oehler

Affiliation: Bytefabrik.AI

I study Applied Artificial Intelligence at the Offenburg University of Applied Sciences and I am very interested in Data Science and AI. During my internship at the startup Bytefabrik.AI in Karlsruhe, I came in touch with the Apache StreamPipes software and became a committer for this project. I work on the python integration to enable easy access to live data streams that can be quickly connected by StreamPipes.

visit the speaker at: Github