Animated data stories in Jupyter & Real-time telemetry-based alerting in A1


Details
Hi all,
Let's come together in a few weeks to see a stunning demo of how you can make charts interactive in Jupyter using open-source tools, and also how A1 analyses the vast amount of data they collect!
Doors are going to open at 18:00 and the talks are going to start at 18:30
Schedule:
- Use animated data stories in Jupyter to present & share your findings with ipyvizzu-story
- Realtime Alarming using Telemetry Records
- Food, Drinks and Chat.
See you there!
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Use animated data stories in Jupyter to present & share your findings with ipyvizzu-story, a talk by Peter Vidos, CEO & Co-Founder of Vizzu (https://vizzuhq.com)
https://www.linkedin.com/in/petervidos/
Description:
Sharing and explaining the results of your analysis can be a lot easier and more fun when you can create an animated story of the charts containing your insights. ipyvizzu-story (https://github.com/vizzuhq/ipyvizzu-story) - a new open-source tool - enables just that with a simple Python interface within Jupyter & other computational notebooks and similar platforms.
In this talk, one of the creators of ipyvizzu-story shows how their technology works and provides examples of the advantages of using animation for storytelling with data.
Bio:
Peter has been involved with digital product development for over 15 years. Earlier products/projects he worked on cover mobile app testing, data visualization, ad targeting, e-learning, educational administration & social. Still, building a selfie teleport just for fun is what he likes to boast about when asked about previous experiences.
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Realtime Alarming using Telemetry Records, a talk by Oliver Leodolter, Data Scientist at A1.
https://www.linkedin.com/in/olileo1/
In order to improve the Service Quality, we need to identify problems in our Network as soon as possible. For that, we gather and analyze Telemetry Records of Client Devices in Real-Time. To keep our solution understandable, scalable and efficient, we decided not to use techniques from Timeseries Analysis and instead developed a solution based on detecting outlier groups.
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Thank you, A1 for hosting this event and providing catering!
Attention attendees with food allergies. Please be aware that the food and drinks provided may contain or come into contact with common allergens, such as dairy, eggs, wheat, soybeans, tree nuts, peanuts, fish, shellfish or wheat.
Zoom is sponsored by CEU:
https://ceu-edu.zoom.us/j/6948707473?pwd=QiszZ01KbzBrRTQvRGpFNGRtR3A1QT09
Zoom and online streaming are set up on a best-effort basis, please come in person if you can!
COVID-19 safety measures

Animated data stories in Jupyter & Real-time telemetry-based alerting in A1