One particularly striking example of an attempt to infer information from seemingly unconnected data was someone noticing that the number of people sick with COVID-19 correlated with how many people were leaving bad reviews of Yankee Candles saying “they don’t have any scent” (note: COVID-19 can cause a loss of the ability to smell):
I found this point of data to be really interesting and honesty a little bit amusing. It is interesting to see how data can indicate trends and major events such as the COVID-19 pandemic. The correlation of bad reviews of candles and people sick might be seemingly unrelated and nonsense information, but is actually an accurate indicator of the effects of the pandemic on people. People who had the virus lost their sense of smell, and that correlated with people not being able to smell the candles and leaving poor reviewed because of that. Visual displays of data like this shows trends and cause and effect relations where one might not usually be able to find.