Author Archives: Chart Planet

The art of colour choices for dashboard – there is no magic, just colour theory

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For those coming to Data Visualization field from Data Science or Computer Science fields, all colour related stuff might seem like magic – either you have an eye for it or you don’t. And if not, then you just don’t bother too much tweaking those, however still admire someone who manages to make a dashboard look nice. Truly a colour magician!
But at the same time, you see when it is getting bad, albeit you might not know how to fix those colours exactly.

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When cool design breaks a dashboard. 8 techniques to avoid.

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We do want to make beautiful dashboards because beauty is attractive, looks tidy, reliable and helps to create impact with our visualizations. But beauty is also just a package – the value of a dashboard is in the way it helps to read the data intuitively. Forgetting all other things except beauty might lead to poor readability and a confusing experience overall, in other words makes users more frustrated than happy.

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What to Consider When Considering the Audience

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“Considering the audience” is one of the most important pieces of advice in storytelling and data visualisation. It is generally suggested to think about their needs, goals, and ability to understand the items displayed in the visual.

This allows our message to reach them more easily and resonate with them better, but the idea of “considering the audience” itself is quite vague.
In this article, I will turn the vague suggestion “consider the audience” into something more checklist-like, which you could go through and consider the audience “considered”.

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How to make a dashboard look cool (and still safe): 10 techniques

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What if your client or stakeholder asks to make the dashboard you prepared to be more eye-catching, beautiful, or just cool? In such cases, we have one job – a very subtle one – to enhance UI without sacrificing UX, dataviz or information designs, maybe even enhancing them altogether.

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Most dataviz best-practices fight one of those three enemies: what are they?

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You can find maybe 1000 articles with “most important”, “essential” or “golden” rules of data visualization and their set will be unique every time.
Here, I will try to extract principles for data visualization from the underlying reasons why data visualization is even a thing.

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