This article shows some practical examples of data analysis from history, including why data-backed decisions are so important.
Data collection and analysis is an enormous industry but it is not a new field.
In this article, we’re going to take a look at some past examples of data analysis to get us thinking: why is data analysis so important, what can we use it for, and how can it help us make decisions?
1. Florence Nightingale
We now see infographics everywhere, but Florence Nightingale was one of the first people to use data analysis and data visualisation to help identify and explain the root cause of an issue.
Here’s her analysis of the causes of death in the Crimean War. Blue signifies cholera and other preventable diseases. Red signifies battle wounds.
Rather than simply treating symptoms, Florence Nightingale looked for root causes, to find out exactly why so many people were dying. She collected data, compared it, and produced this chart to illustrate the cause of death.
You can clearly see that preventable diseases vastly outweigh battle wounds.
Florence Nightingale used this to determine how medical resources should be allocated and how hygiene practices should change to reduce suffering and illness.
2. John Snow: Cholera Outbreak
Similarly to Nightingale, John Snow used data collection and analysis to aid understanding of the transmission of severe illnesses. In 1854 there was an outbreak of cholera in London.
At the time, bad orders in the air were thought to cause illness, including cholera. John Snow’s analysis showed that the cholera outbreak actually came from a single contaminated water pump.
Using data to determine the cause
Rather than reiterating received wisdom, John Snow may have asked of his data: what’s causing this outbreak, or where specifically has this outbreak come from and how can I see it in the data?
Using data to determine the cause, even the precise location of the outbreak, allowed Snow to change medical understanding and public hygiene practices.