Scalar 2017

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.

Did you enjoy reading this article?
Would you like to learn more about leveraging AI to drive growth and innovation, software craft in data engineering, and MLOps?

Subscribe to the newsletter or add this blog to your RSS reader (does anyone still use them?) to get a notification when I publish a new essay!

Newsletter

Do you enjoy reading my articles?
Subscribe to the newsletter if you don't want to miss the new content, business offers, and free training materials.

Bartosz Mikulski

Bartosz Mikulski

  • MLOps engineer by day
  • AI and data engineering consultant by night
  • Python and data engineering trainer
  • Conference speaker
  • Contributed a chapter to the book "97 Things Every Data Engineer Should Know"
  • Twitter: @mikulskibartosz
  • Mastodon: @mikulskibartosz@mathstodon.xyz
Newsletter

Do you enjoy reading my articles?
Subscribe to the newsletter if you don't want to miss the new content, business offers, and free training materials.