A workshop student asked me for places to go to see collections of great data viz (he said he goes to Reddit's dataisbeautiful 🫤). I asked my LinkedIn followers for their suggestions and this is a thread of their go-to viz inspo spots.
I said go to Twitter and search on #dataviz or #datafam. Someone else in the workshop mentioned Tableau Public.
Brian O’Connor wrote:
Agree with Tableau Public as source - some favorite authors include @flerlagekr, @FlerlageKev, and Ryan Sleeper.
Lydia Hooper said:
My go-tos are Flowing Data, Mona Chalabi, The Upshot (NYT), and anything Alberto Cairo recommends
Lindsey Peterson pointed to a specific Flowing Data piece she likes:
Here's one I have enjoyed for several years, showing animated commute data: flowingdata.com/2017/05/17/ame…
Ryan Estrellado added:
Awesome post! I like FiveThirtyEight and The Economist. I’ve been using them as a reference lately for styling tables.
Gene Shackman:
This Gallery of Data Visualization displays some examples of the Best and Worst of Statistical Graphics, with the view that the contrast may be useful, inform current practice, and provide some pointers to both historical and current work. datavis.ca/gallery/
Julia Krolik wrote:
Information Is Beautiful submissions and winners
Kevin Paquette added:
I recommended the books, "Effective Data Visualization" and "Presenting Data Effectively". The author's name slips my mind.
(Bonus points, Kevin)
What else would you add?
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I didn’t record my @OutlierConf unconference session on starting and growing a 6- or 7-figure #dataviz business, so here’s a thread of the main discussion points.
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@OutlierConf Should I niche?
Yes. It’s vastly easier to pitch, market, and resonate when you have one specific audience you’re speaking to. You can niche by content area (like education or public health), by tool (like Tableau or Power BI) or by style (like static utilitarian or data art).
How do I price my work?
This Q is often asked too soon. Focus first on defining and understanding your niche. You’d price different if you were pitching to Tiffanys versus Walmart, you know? Both are totally cool, you’d just price different.
What makes a dataviz suck or sing isn't just about its outward appearance. That's only going to get you so far and it isn't even the most important part.
The most important part of data visualization is what happens to people after they've seen it. 👇
Like, if your audience asks about things you already addressed.
8 things school doesn’t teach you about data visualization.
1. Design is always a compromise. Rarely does the real world gift you with the perfect datasets you work with in school.
1/8 🧵
2. The longer you’re in it, the less you know for sure. “It depends” is the one true answer 99% of the time.
3. You can figure out what “it depends” on if you listen to your audience and their intended goals. Don’t ask what they want in the dashboard, ask what their goals are.
Now that I have your attention, I'd like to address the non-Black folks who are saying they wish they knew what to do right now.
I'll tell you what I have done, not that it is an exhaustive list (never will be) to give you inspiration and ideas.