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Radio and data analytics: surprising similarities from mic to mouse

A neon sign on a brick wall reading 'This is the sign you've been looking for'

This post was originally published on The Data School blog between 2018 and July 2025, before our program was renamed to MIP’s Analytics Career Accelerator. References throughout this article to “The Data School” or “DS” all refer to what is now MIP’s Analytics Career Accelerator. The program, its people, and its commitment to launching outstanding analytics careers remain the same – just under a new name.

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Have you ever felt like it was time for a career change but you weren’t sure where to start?

That was me in early 2022. I was working in radio and although I loved the thrill of the news cycle, I felt like something was missing. Cue: a serendipitous LinkedIn post advertising a job in data analytics (complete with four months paid training… you see where I’m going with this.)

Despite being intimidated by the thought of transitioning to a completely different field, the more I thought about it, the more the commonalities of the roles stood out.

Both journalism and data analytics rely on gathering and analysing information to tell a story – diving down the rabbit hole to get the context and working out what you need to communicate your narrative in a way that resonates best. Whether it’s crafting a human-interest story for your audience to engage with on different platforms, or exploring and visualising data sets, both fields require a critical eye, and both need to present information in a clear way.

The goal is to communicate complex information in a way that is engaging and accessible for your audience. This requires a good understanding of the subject matter and an ability to translate technical information into plain language. It also means being able to explain why something matters and having evidence to back that up.

Communication is my specialty. The technical acumen is something I’m looking forward to developing (with the help of several seasoned professionals and a cohort full of tech wizards) as we embark on our training.

Now, I won’t lie – we’re only just begun our second week and transitioning from radio to data analysis feels like a learning curve of mountainous proportions. The pace is nothing to be sniffed at. But despite the challenges (of which there are many) I have no doubt that facing these difficulties early on will come in handy as we navigate the wider world of data analytics, particularly when it comes to teaching others the tools.

For the next four months, DSAU19 will be keeping you updated with the latest challenges we face and the insights we glean.

 

 

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