An Interview with Lorna Eden

by Andy Kriebel

We’re continuing our “An interview with…” series today, where we speak to members new and old from The Data School to understand what a career in Data Analytics looks like. In today’s installment, we speak to Lorna Eden of The Data School’s 2nd cohort (DS2) about her first experiences with data visualization, Tableau and The Data School. But before we completely ruin the surprise, we’ll let Lorna take it from here!

Thanks for making time to speak to us today, Lorna. To start off with, what were you doing before you joined The Data School?

“I was still in the process of graduating from university; I was doing an MSc in Sports Sciences at the University of Chester and I was also on a placement with British Gymnastics with the English Institute of Sport at the same time. So busy!”

So you hadn’t really been involved in data in any capacity before The Data School?

“A little, but only on the research side of things through my undergrad and postgraduate courses. It was actually my time within British Gymnastics that I really began to get involved – they were the ones who introduced me to Tableau. Using it with the coaches and the gymnasts allowed me to see the real-world effects of Tableau. They could see their data better than they could with just a bunch of numbers and raw data.”

Was it a bit of an eye-opener in what you could see through the power of data?

“Yeah it was so interesting to see how much more you could get from your data by exploring it more, as opposed to just looking at the numbers or something you could get out of, like, Excel.”

Speaking of Excel, was that your only prior dealings with a product that lets you work with data?

“Yeah, previously, it was pretty much all Excel-based; so I was either dealing with big spreadsheets or having to pull stuff from PDFs.”

Comparing Tableau with Excel, what were your initial thoughts of the tool?

“It was just so much easier and quicker to get more from your data; you were able to get what you wanted within just 5-10 minutes. After using it the first few times I wanted to get better, so I mainly just self-taught myself, watched lots of tutorial videos and also attended a couple of Tableau webinars to get myself more accustomed to it all.”

What made you want to join The Data School course in particular? Is there anything that stood out for you?

“I wanted to use Tableau in a bigger, broader sense after I’d spent some time getting more familiar with the tool, and being able to easily clean up my data with Alteryx was something that appealed to me, too. The Data School was the perfect place to learn.”

Had you heard of Alteryx prior to that?

No, I hadn’t actually, but I’d read about it in the lead up to the interviews. The course was my first chance to get hands-on with it. Looking at it now I wished I’d had it earlier as it would have saved a lot of time with my uni dissertations!” (laughs)”

Hindsight is a wonderful thing! If Tableau was the big draw, how did your decision to go with The Data School come about?

“It was actually through a Sports Analyst website where the role was advertised. It was enough to get me interested, so I went and did all my research and after I knew more about it I thought “that’s the thing for me, I need to join it”. And luckily I got to!”

You used Tableau at British Gymnastics. Was data an area that you’d always wanted to go into or was it spurred on when you saw what could be done?

“I think I always had some degree of interest, you know, but I think once I saw what could be done with Tableau and the power of the tool at the time it definitely spurred my decision on. I was pretty certain that this would be the best way to excel my knowledge with Tableau, as well as obviously all the collateral that comes with it.”

Talking a bit about the present, what’s the best piece of advice that’s been given to you at The Data School?

“Practice, practice, practice. Get things from Tableau public, tear it apart, rebuild it so you understand the concept in a personal sense and then have that knowledge in your bank. It helps to see exactly how the visualizations have been built, so you can then build them for yourself. I work it through a step-by-step process, almost. It’s as much about working with old and used sets of data as it is about brand new data sets. When it comes to creating an original visualization, you need to have previously dealt with other data viz’s, for both the inspiration aspect and then practical building side of it.”

On The Data School blog you get ‘waves’ of posts like “TipWeek” and “DashboardWeek”; how intensive are those exercises?

“Dashboard Week in particular was hard work. Each morning we were given a data set and had to build a dashboard in the day, and the next morning we would present that dashboard. Then we’d get a new data set, and then rinse and repeat. Friday was the hardest because we had to present in the morning, build something before 3pm and then present everything from the whole week. I found it hard to fit everything in one blog but it was a great learning exercise. It’s a profession where you’re often under pressure or working to deadlines so it was really useful.”

Had you blogged before you started at The Data School? Was it relatively new?

“In a sense, yeah. Going back to being really scientific in my writing [at University] where everything had a rigid structure and I had to reference every point I wanted to make, the blogging has much more of a personal side to it. I haven’t found it too bad, I think it’s more a challenge of finding new areas to blog about because you don’t want to repeat something that has already been done unless you have a new or different take on it.”

With only a couple of weeks left, what are your feelings on graduating from The Data School?

“I’m looking forward to getting out into a company and experience working, definitely. I’m a little bit scared (laughs) – I don’t feel like we’ve been here the full four months let alone ready to go out into the real world! But no, I’m looking forward to it and I know that I always have support from the coaches here, and that I can just pick up the phone if I need some help or advice.”

To finish with, then, what would be your perfect role upon graduating?

“I would love to take it back into sport, and be able to implement it across sports science, the business side of sport, and then… well just sport in general! (laughs) I think it’d be good to make a difference within the world of visualizations because I think that’s an area that’s lacking at the moment.”

What do you think you’d bring into a sporting environment having learned Tableau and Alteryx?

“I think mainly the visualizations, and the access to data that people haven’t seen before, but also showing the different things you can actually do with Tableau. Being able to teach practitioners how to deal with the data themselves, and actually see what’s going on in the massive collections of data they deal with on a daily basis. It could give a lot of added insight, I think.”

To get a further look at life behind the Data School doors, check out our blog for more insight from other members old and new!

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Andy Kriebel

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