Good Charts

but it benefits from collaboration and borrows on design thinking processes: gathering as many diverse points of view and visual approaches as possible before homing in on one and refining it.

That is, choose the visual form that will most efficiently and most accurately convey the data’s meaning.

The more relevant a data visualization is, the more forgiving, to a point, we can be about its execution.

That approach might be fast, and it might spruce up the look of a chart, but it doesn’t refine the ideas that the chart conveys.

Digital prototyping is rapid prototyping. It’s especially powerful for confirmatory and exploratory dataviz.

Adjust what’s around it.

What makes that version simpler?

So instead of jumping right to chart types and design, you need more inputs to help define your context and identify the visual approach that will be most effective.

One day in class he showed his visualization and then, when he was ready to say something that the students needed to hear, he shut off the screen entirely. The effect was stunning. Eyes that had been fixed on the picture darted to him and locked in. With nothing else to look at, the students listened intently.