Stunning Business Intelligence Visualizations… from 1870


FastCompany has a great article this week on the results of the 1870 census, and the hand-made graphics (“BI –2.0”?) that were made from the data (thanks to and the Library of Congress). [NOTE — the original version of this post erroneously said “1830” throughout]

Here’s a selection of my favorites – click on each one to get the full graphic.

US geology – the hand-shading is so much nicer to look at than computer-generated graphics:

1830 census map

Nationality data mapped:


There’s a lot of history illustrated in this fiscal chart:


This is a beautiful rendering of church-going in the US. Interestingly, rather than show non-churchgoers as a separate bar, they are relegated to a grey box around the outside.


Here’s a nice example of showing data through proportions.


And here’s proof that men are bigger idiots than women! (of course, they meant what we’d call “mentally ill” these days)

1830census pie idiocy

1830census insanity

Population charts showing that the “cowboy states” (e.g. Wyoming, Nevada, Montana) were populated by young male foreigners, while Utah had LOTS of children.


This chart is a good example of something that hasn’t changed much in the last couple of centuries – the notion that you should show data just because you have it. For example, Chart 1 below show deaths per month per state. Is this data actionable in any way?


Later charts aren’t nearly as attractive, like these, from the 2000 Census:


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15 Replies to “Stunning Business Intelligence Visualizations… from 1870”

  1. Would be nice to have a ‘retro’ pack to create visualisations like this.
    I’d like to see those paper wrinkels in my charts. If it’s old, it’s probably true :^).

  2. Interesting stuff – shows that visualization of data is not anything new. I would take issue, however, with your statement regarding the notion that mortality information isn’t actionable? Lots of health service and infrastructure planning relies on this kind of information. Would indicate where I need to be sending doctors and medicine, building hospitals, etc. And almost every entity that tracks growth information, (sales, income, units), needs to net out costs/losses to really understand what’s going on.

    1. John, I think you’re illustrating my point. In general, yes, mortality data is useful, of course. But just because data is useful in theory doesn’t mean that a specific data set is going to be useful in practice. In this case, it’s deaths by month, which isn’t going to help much with the number of hospitals, etc., and more importantly, given the differences between all the states, it looks like a snapshot of randomness, and that’s not going to help anybody with their planning… Actually, that’s another point — a lot of companies DO try to plan today using data without taking into account of random variation.

      One of my pet themes is that BI has to take better account of “fuzzy” data, helping average business people determine what’s real and what’s just noise. Experts can do this today with the right tools, but we need the application to do more of the expertise for us — and this is probably only possible in the context of an application (another reason why BI and ERP go together well)…

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