Podcasts have become absolutely integral to my daily life. I often start the day listening to something inspirational with my morning coffee. In normal times, my commute to work offers the perfect length of time for a podcast episode (sadly reduced to 20 steps currently). I often potter around the house gardening, cooking or tiding while listening to some podcast in my free time.
In my day job, I spend a lot of time with sheets of data and cleaning them, so they are analysed correctly. If you have ambitions of becoming a digital humanist or data visualiser, you too will likely spend the vast majority of your time this way. Thankfully most of the data-wrangling operations become a bit rote after a while. This has provided me with the perfect environment to multitask and enhance my skills by listening to a podcast episode. Indeed, some of the data cleaning workflows I now use were inspired by hearing about some tool or process.
One of the biggest challenges of combining the fields of humanities and data visualisation is keeping up with the current trends and technologies. As a historian, I have a pile of books, papers and documents which I need to read to produce research in that discipline. At the same time, the technology world does not wait for me. It moves on at a relentless pace, with new trends, tools and stacks emerging all the time. Podcasts have provided me with a means to keep up with what is going on in the tech world.
When asked how to get into data visualisation, I always emphasise that it is like learning a foreign language. You have to get comfortable with the vocabulary. The number one skill you should absolutely cultivate is communicating what you want to do, why you want to do it, and how you are thinking of doing it. This enables you to google a solution or tutorial, reach out on social media, or ask colleagues for assistance. Podcasts are fantastic for helping you get a grounding in the terminology of a discipline. Listening to others discuss what they have built, why they have built it, or hear about their learning journey has been an invaluable resource for me.
In this post, I thought it might be helpful to lay out some podcasts I have listened to over the years and have inspired and taught me so much. I would highly recommend these to anyone looking to start out in data visualisation.
So, in no particular order:
This podcast is hosted by Cole Nussbaumer Knaflic, who has written some great books on data visualisation. Each episode features a guest speaker and thematic topic - from maps to effective presentation techniques. An excellent episode for beginners to data visualisation is “What is Data Visualization?”
Podcast hosted by Enrico Bertini and Moritz Stefaner. It provides engaging discussions of many of the topics within the field of data visualization, so it is a fantastic way of building up your reading list. Check out “Edward Tufte’s complete work with Sandra Rendgen”
Learning to code for the first time. No problem. Inspiration and ideas on how to begin your journey are available in this podcast from industry leaders. Accessible introductions to many programming topics are available, which is great if you are still trying to work out what solution might be best suited to a particular problem. From “How to communicate complex technical topics” to “What you need to know about APIs”.
Hosted by Laurence Bradford, this podcast provides another great entry point into the world of coding. Often has inspirational episodes that feature a guest who has transitioned into the world of tech from another industry. Check out “From Glassblower to Software developer using Free Coding Resources with Michael Pimentel” for a taste of what is on offer.
Long running podcast on machine learning, artificial intelligence and various data science topics. Features deep dives from experts and introductory overviews of different tools as well. Check out “The Path the Data Visualization” or Using Data Visualization Tools SuperDataScience
I hope you may find this post useful. Feel free to let me know what podcasts you subscribe to.