I was throwing away my ex-husband by mistake

I was throwing away my ex-husband by mistake

Yesterday, I attended a networking lunch at Google Zurich and had the chance to talk with Luisa Barbanti about data science. Chatting with her reignited my passion for this field – really, it’s a love affair with Mathematics. I’m even planning a deep dive into the world of maths when I retire.

Eduardo Oda once shared an intriguing perspective with me: Math is the relationship between elements or sets. It’s like telling stories using numbers. In this light, Data Science feels like a Shakespearean tragicomedy. It’s fascinating, yet I can’t help but notice how people sometimes get lost in the numbers, forgetting to peek behind the curtain at the storyteller or their incentives.

Here’s a quirky example: I once embarked on a mission to track the words I discarded in the trash can – call it a linguistic treasure hunt. These discarded words found a new home through my scanner, getting a digital rebirth. Before the era of ChatGPT, I used optical character recognition (OCR) to transcribe the words.

To visualize this eclectic mix of words, I used Processing, a flexible software sketchbook and a language I use to teach how to code. Processing is an excellent tool for designers, promoting software literacy within the visual arts and visual literacy within technology. Specifically, I used an SVG icon of a trash can as a mask for my word cloud.

Crafting a word cloud from this eclectic mix, one name leaped out: “Paulo”, my ex-husband’s name. A mystery unfolded – why was his name frequenting my trash? The plot twist? It wasn’t “Paulo” but “São Paulo”, the vibrant city I was living in. A comical mix-up, but it revealed a profound truth: context is everything in data science.

It’s not just about the numbers, but the stories they tell and the sources they come from. It’s a lesson in checking our facts, or we might end up accidentally throwing away something – or someone…

Thanks Luisa for reminding me of this. I found a captured video of my screen at the moment I was trying the idea in February 2018. I hope you enjoy :)

What Did I Learn From This?

• Importance of Context: Understanding the context of data is crucial to avoid misinterpretation and incorrect conclusions.
• Data Interpretation: Data science involves not just analyzing numbers but also interpreting the stories behind them.
• Verification: Always verify assumptions and check facts to ensure accuracy in data analysis.
• Meticulous Approach: Handling and interpreting data requires a meticulous and thoughtful approach to capture key details and avoid mistakes.
• Continuous Learning: Engaging in conversations with experts and revisiting fundamental concepts can reignite passion and deepen understanding in the field.