The Good Data Project @GoodDataProject
Bad data confuses and obscures. Good data tells stories and illuminates the world. A @Nate_Elliott / @19insights project. GoodDataProject.com Joined August 2021-
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Did you know Latvian women are *21 times* bigger than Indian women?
Is it possible @JamesClear has sold 15 million copies of a book containing nothing but made-up charts and graphs? Apparently it is: gooddataproject.com/blog/2024/5/at… #data #dataliteracy #atomichabits h/t @The_Law_Boy @RottenInDenmark @IfBooksPod
602,000,000,000,000,000,000,000 doesn't mean anything to most people. But describing a huge pile of candy might. @nate_elliott on the value of concrete examples:
The best way to explain an abstract number? Encourage your readers to imagine something concrete and familiar. The @GoodDataProject explains: gooddataproject.com/blog/2024/4/60… h/t @karlastarr Chip Heath @MeganBurnsCX #data #dataliteracy
No, I can’t do this kind of math either. And that's the point: Even when causation seems obvious, you need to do the homework and the math. More from The @GoodDataProject: gooddataproject.com/blog/2024/4/ca…
They're easy to make and easy to read. What's not to love? Read @nate_elliott's valentine to square pie charts:
I think square pie charts are amazing. @McKinsey agrees. (I always knew those guys were smart.) Learn more from The @GoodDataProject: gooddataproject.com/blog/2024/4/wh…
Claiming that one thing caused another is one of the most powerful – and most tempting – forms of data storytelling. Some cause-and-effects just feel so clear. Just one problem: It's basically impossible for normal people to determine causality.
Flint poisoned its students with lead, and test scores plummeted. It seems obvious the lead caused the low scores. But proving causation is rarely that simple. The @gooddataproject digs deeper. Hat tip to @kdrum. gooddataproject.com/blog/2024/4/ca… #data #dataliteracy
Beware of those who claim “up to” - whether describing their sales discounts or their ability to stop deadly diseases, they're only showing you the very best-case scenario.
Whenever someone claims their product or service or sale is “up to” something, you can be pretty sure *they’re* the ones who are up to something: The @GoodDataProject reviews PhageLab's pitch deck (via @TechCrunch ): gooddataproject.com/blog/2024/4/ne… #data #dataliteracy
The Data Story Mandate tells us data stories must be correct and reliable, but they also must be meaningful. When you explain your data, rather than just describing it, you add that meaning.
Anytime you start a sentence with “as the following chart shows,” you’re probably not adding much value. The @GoodDataProject on how to explain data rather than just describing it, featuring @StatistaCharts: gooddataproject.com/blog/2024/4/do…
"Check and double-check and triple-check your data. One day soon you’ll be glad you did."
If data companies sometimes get their data wrong, you can be certain marketers and journalists do as well. The latest from the @gooddataproject: gooddataproject.com/blog/2024/3/ch… #data #whitepaper #researchpaper
It’s amazing how much online “wisdom” is actually complete garbage.
It's a shiny bunk nugget! gooddataproject.com/blog/2024/3/sh…
@dailycopywriter Please stop using data you can't source. None of these statements appears to be true. Nothing good happens when you use unsourced data: gooddataproject.com/blog/2024/1/st…
When someone tells you they've fabricated their data, listen to them. (About the fabrication part, that is.)
There's at least an 80-90% chance I made up the numbers you're reading right now. The @GoodDataProject explains how to spot fabricated data: gooddataproject.com/blog/2024/3/th…
There's at least an 80-90% chance I made up the numbers you're reading right now. The @GoodDataProject explains how to spot fabricated data: gooddataproject.com/blog/2024/3/th…
Every day I encounter data stories that are both technically correct and wildly inaccurate. How is that possible? The Good Data Project explains: gooddataproject.com/blog/2024/3/ho…
The marketer (or tabloid headline writer, or great American novelist) inside you might desperately want to make a data headline better -- but there's a good chance that'll make your statements wrong.
There's a simple reason so many data statements are inaccurate -- and two easy checks you can use to fix them. The @GoodDataProject's latest post features legendary novelists, pregnant dolphins, and even some advice about good data. gooddataproject.com/blog/2024/3/wh…
@FastCompany featured the @GoodDataProject's working on the importance of data sourcing. Go check it out, share it, etc etc: fastcompany.com/91023619/8-sec…
In their defense, they really gave it 110%...
Maybe let's not trust a data source named Pig In A Wig? Unfortunately, @betterhelp did. The @GoodDataProject explains: gooddataproject.com/blog/2024/2/ab…
Organizations use lots of data storytelling tricks to make sure they look great. @nate_elliott explains how to make sure you don’t repeat brand-funded nonsense:
When Muhammad Ali said “I am the greatest,” the world believed him, because he was. But there are lots of reasons we shouldn’t be so accepting when others tell us how great they are. Check out the @GoodDataProject for more: gooddataproject.com/blog/2024/5/i-…
Lots of things *used to be* true. George Washington used to be president. Jerry Seinfeld used to have a TV show. My mom used to sell Avon. But even good data expires. The @GoodDataProject explains when to let go: gooddataproject.com/blog/2024/1/fa…
@nate_elliott on the goldfish myth, and what it tells us about data storytelling
One of the most quoted and compelling data stories of the past decade appears to be a myth. And I bet you've repeated it yourself. The @GoodDataProject has the story, and its lessons: gooddataproject.com/blog/2024/1/st…
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