I can either spend next three hours writing a 600-word long text or just quickly write a list of all the talks I liked, download a new dataset from Kaggle and play with it. It is easy to choose, isn’t it? ;)
Talks I liked
Tracing Akka Streams (Raam Rosh Hai)
A great tool! The speaker was probably a little bit afraid of speaking in front of the audience, but it does not matter. His project is exactly what I was looking for.
Real-time anomaly detection made easy (Piotr Guzik)
That was a quick win, I love everything related to data science and machine learning ;)
Machine learning by example — workshop (Michał Matłoka)
It was fun, even though I have not learnt anything new.
Kontextfrei: a new approach to testable Spark applications (Daniel Westheide)
Solves my problem, that is enough for me ;)
Building a real-time auction engine using event sourcing (Alan Johnson)
That is why we attend conferences, to hear a good story, something based on real-life experience.
Carpenters and cartographers (Valentin Kasas)
Selling domain driven design in a very metaphorical way. Also Valentin was not afraid to criticize The Gang of Four and the design patterns. I appreciate that because sometimes I feel we have too much dogma in IT.
Lambda core — hardcore (Jarosław Ratajski)
Pure awesomeness. Wizards, rainbows, unicorns, and lambdas.
The most important thing
For me Scalar was a “combo-breaker”. I was disappointed with the last 3–4 IT conferences I had attended. Usually when someone asked about my opinion, I was saying: “If I had bought the ticket with my own money, I would be outraged”.
Scalar is different. I highly recommend attending the next edition.
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- Data/MLOps engineer by day
- DevRel/copywriter by night
- Python and data engineering trainer
- Conference speaker
- Contributed a chapter to the book "97 Things Every Data Engineer Should Know"
- Twitter: @mikulskibartosz