
Infografikas yra sukurtas projektui “Mitas”.
Sukurta su Figma.
I also want to be a self-respecting dataviz educator, so I will write an article about pie charts. But instead of just explaining why they are good or bad, or how to use them, I will use it as an example of generic dataviz advice, highlight why they might be poor, and whether you should still follow them.
CONTINUE >>>If you have been on the internet recently, you might have noticed that dashboards are dead because now we have AI (Artificial Intelligence). But we, people in data, still consider AI as a solution looking for a problem.
CONTINUE >>>I will cover one thing you have to consider when choosing colour to make reports more accessible. In the end, I will provide one technique how to utilize it beyond just accessibility – for better guiding of the audience.
CONTINUE >>>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.
You might have heard multiple times, that beautiful dashboards are attractive, memorable and people want to spend time with them. But more often, it is enough for your dashboard just to look professional.
CONTINUE >>>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.
CONTINUE >>>“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”.
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.
CONTINUE >>>