Remember those old Apple ads that listed off random daily tasks and hey – turned out “there’s an app for that”?
I think “data” is the new “app.”
Today you can find datasets on:
- Every move in every recorded chess game since the 10th century
- The entirety of Open Library’s holdings
- The ingredients of all foods sold in the US
- Comprehensive US opinion poll, epidemiological, employment, and economic data
- Endangered and extinct world languages
- Social interactions between the 62 dolphins living in a pod in New Zealand
- More than 80,000 global UFO sightings over the last century
Admittedly, some datasets may be more useful than others. But the point is that they’re out there – we’re swimming in datasets large and small.
This data availability is an amazing opportunity for nonprofits to find new avenues for change, but it’s also a lot of noise to sift through – and a daunting task if you don’t know where to start.
Data for autodidacts
I was born in 1984, which puts me in the first few years of the Millenial generation (I guess the “Generation Y” label didn’t have enough staying power). I went to an excellent school and leaned far into the sciences, yet I don’t think graphs or data visualization were ever formally taught. Perhaps enough to get us through that week’s homework assignment, but that was it.
I imagine the same was true for you, too. Unless you specifically studied statistics, data visualization was just a brief stopover in the sciences (assuming you even studied the sciences) and math. Graphing was simply a tool to get results on the page because –ugh- the teacher was making you. It wasn’t something to focus on.
With a greater emphasis on technology and capacity to collect data, however, that trend is shifting. With more data comes a need to better understand that data, putting data science in higher demand.
Universities are scrambling to fill the gap, offering new degree programs in data science and beefing up their data education in science-based degrees. But is that kind of major change necessary? Do you need to dive headlong into the world of statistics and programming to glean insight from the data glut?
The good news: There’s a lot of help for the self-taught
The number of resources for self-learners is growing rapidly. Just as formal universities are raising fine crops of data scientists, so too is the informal education sector. Online course hubs like Coursera, Codecademy, Udacity, Udemy, and others offer data science courses for free or on the cheap.
A proud autodidact, I elected to pursue this DIY route. It’s a path I feel is entirely doable, though I realize it’s not for everyone.
The bad news: That first step is a doozy
Many of these resources are aimed at those with some experience in programming. Not a programmer? You’ll have to go back a few levels and learn first. I do think learning to program is a great skill, but that’s a daunting hill for anyone to climb – especially if you’re already busy with so much other nonprofit work.
From what I’ve seen, there’s a vast chasm between basic Excel skills and advanced interactive data visualization – no middle ground for the beginners and intermediate learners to explore.
Help nonprofits, help the world
I started Hypsypops because I saw a need in the nonprofit sector for better data-based communication and greater data literacy. But of course, just because there’s a need doesn’t mean there are resources for organizations to learn or contract these additional skills.
I’m hoping to bridge that chasm and give nonprofits a shortcut between early steps and advanced programming. Let me know how I can help – what data skills do YOU most want to learn?
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