Hi everyone, welcome to the November edition of Docker Birmingham!

This month we'll be following on from where we left off a few months ago (doesn't time fly) with the continuation of the data theme and how containerisation can help with putting scientific methods centre stage when working with your teams.

Agenda

18.00 - Gather, network, chat, laugh, drink, nibble!
18.30 - Matt Todd - Make Data Science Great Again (Part 2)
19.45 - Discuss, pub, more chat!

We hope to see you there!

Speaker

Matt Todd - Make Data Science Great Again (Part 2)
This talk will pick up where the last session left off and take a look at how some of the more heavyweight components in the Data toolbox can be orchestrated and shared with your fellow data engineers.

I'll cover the usual suspects which could be part of a typical data platform - Jupyter, SparkML, Flink, Kafka etc and how they can be wired together to create small scale versions of potentially large scale deployments. This approach will allow for more accurate testing and performance evaluation on sample datasets before a full run is performed at scale.

The principles of reproducibility and repeatability are key to this process and one of the key benefits of using lightweight "virtualisation" technologies such as Docker. Using declarative infrastructure definitions reduces complexity and setup time yields more time focussing on delivering information for business decisions and less time aligning environments.

Bio

Matt is a technologist with a background rooted in a love of computer science and AI, having worked with a number of companies both tiny and huge to design and deliver technology solutions aligned with delivering real business value.