When John Snow Used Dots to Beat Cholera: The Birth of Data Analysis

Imagine solving a deadly disease outbreak with nothing more than pen, paper and dots on a map—that’s exactly what Dr John Snow did in 1854 London. By pinpointing cholera cases on a street grid, he unknowingly sparked the field of data analysis: the art of extracting insights from raw numbers. In this post, we’ll trace its surprising roots and show how data analysis shapes our world today.

A brief history

Back in 1854, John Snow mapped over 600 cholera cases on a London map, using simple dots to reveal a cluster around the Broad Street pump—and convinced officials to disable it. His clear visualization is often cited as the first use of data analysis in epidemiology. A few years later, Florence Nightingale took those ideas to hospitals, creating her famous 'coxcomb' charts (a type of pie chart) to push for sanitary reforms—showing that good data visualisation can change minds and policies.

Where you'll see this in real life

Data analysis isn’t just for 19th-century doctors. You’ll bump into it all the time: - Public health: Tracking flu outbreaks or predicting COVID-19 hotspots. - Sports analytics: Teams use player metrics to plan game strategies and sign new talent. - Streaming services: Netflix and Spotify recommend shows and songs based on your viewing and listening history. - Environmental science: Scientists analyze temperature and CO₂ data to model climate change and forecast weather.

Tips for mastering data analysis

Ready to level up your data analysis skills? Start by asking clear questions—what do you want to uncover? Next, organise your data neatly: check for blank entries or typos. Then, visualise early: charts and graphs often highlight patterns before you run the numbers. Finally, stay curious and question whether your findings fit with what you see in real life.