Softwire Lightning Talks, Data Engineering edition: Six experts in sixty(ish) minutes
It’s time for a whirlwind jaunt through six hot topics in Data Engineering with experts from Softwire and friends!
Expect intelligent summaries of what’s going on in Data Engineering, alongside giant timers, questionable PowerPoint graphics, and obnoxious klaxon noises when time is up.
There will be time for audience questions in between the talks, then time for networking fuelled by more free pizza and drinks than you can shake a reasonably large stick at.
Come to our office in Kentish Town on April 11th and watch our experts take you through these topics in six minutes each:
Why is everyone talking about vector databases, and why does it matter?
The story of how sci-fi hyperspace became part of my day job.
Ant Pengelly
Whether belting out tunes in musicals or teaching machines to sing their own kind of song, I find harmony in the juxtaposition of York’s timeless charm and the relentless march of innovation. With my trusty cocker spaniel, Holly, by my side*, allow me to sing** you a tale of data.
*Dog not guaranteed
**Singing not guaranteed
What to do with 20 million pictures of eyes?
Have you ever found yourself with millions of images of eyes across 10s of formats and 100s of drives and a desire to do some groundbreaking science with them? If so I have a quick and easy* solution for you!
*solution may not be quick or easy but guaranteed to be interesting.
Alice Selway-Clarke
I’ve been working here for just over three years and am super excited to have been given this opportunity to talk about the awesome technology we get to work with.
I love Data Engineering because it has the power to transform chaotic and disorganised real-world data into clear and valuable insights. When I’m not strapping together parts of GCP architecture I am a keen crafter (part of the large Softwire crochet contingent) and cold-water swimmer.
Smoking and lung cancer: getting the most out of limited data
Recent small-cohort medical data have suggested new and unexpected mechanisms for how smoking causes lung cancer. Understanding this process could help us to prevent lung cancer or catch it early, but there’s not nearly enough for a machine learning approach.
I’ll be talking about how I’ve used mechanistic modelling approaches to get more information from limited datasets by leveraging what we already know. I’ll also mention a few pitfalls this sort of approach can bring, and the kind of testing infrastructure that can get around them.
Hugh Selway- Clarke
I’m speaking here based on my own merits as an interesting data-man and entirely independently of my marital status.
So you think you have a data problem?
Data is everywhere, but data engineering problems come in lots of different shapes and sizes – and it helps to know what category your problem might fall into.
Laura Hughes
Throughout my studies it became clear to me that what I enjoy the most is solving problems, simplifying solutions and creating order from chaos – all reasons why I feel very much at home in the world of data engineering. As a technical principal, I design technical solutions to complex data problems. In the rest of my life, I’m a founding member of a somewhat critically acclaimed post-garage-punk band.
How to get the least out of your data pipelines
Do you hate your data? Want to get the least out of it you possibly can while spending as much as possible?
Well today is your lucky day!I’ll cover some quick actionable tips to go from streamlined, stable, observable data pipelines to what could only be described as “Data Spaghetti”.
I suppose this might also be helpful for people who want to avoid pitfalls when working with data too…
Matt Barnfield
This started all the way back with recreational spreadsheets as a child, through my master’s thesis on reinforcement learning, to my role now as a Senior Data Lead.
I love that Data Engineering is really only just getting started. Every week we’re finding new ways to organise and use data, and often it directly impacts the real world.
In my work with Moorfields Eye Hospital, we’ve categorised and anonymised a petabyte of imaging data to enable research such as early detection of Parkinson’s.
Outside of work, I enjoy making video games- particularly in game jams, where we make an entire game in a 72 hour scramble!
Seeing strokes at speed
To detect brain injuries in ambulances, we’re collecting large amounts of new data. Processing that data fast enough for emergency medicine means looking at what is needed to give actionable clinical insight and how to get that answer ASAP. I’ll talk about our data pipeline and address why we might not want to just throw ML at everything straight away, and point out the parts where we might once we’ve validated the approaches.
Patrick Beldon
Agenda
- 18:00 – Arrival, welcome drinks and snacks
- 18:30 – Lightning Talks start, with Q&A in between
- 19:45 – Pizza, drinks and networking
- 20:30 – Carriages
How to book
Our Lightning Talks are free to attend! But places are limited, so please reserve your spot as soon as possible.
Get your free ticket nowMore information
For anything else, please get in touch with me, Helen Jackson, by emailing [email protected], or grab me on X or LinkedIn (including if you’d like to opt out of receiving future marketing communications from Softwire).
Please also note that filming/photography may take place at this event for promotional and archival purposes. The photographs and recordings made are likely to appear on our website and social media (If you would prefer not to be photographed please let the photographer know on the night).