A few months ago, I outlined data-viz lessons in photography. As I shared then, it’s importance to design a viz with an intent in mind; a viz should answer a question or test a hypothesis.
However, sometime this approach does not work. In those cases, it becomes much more difficult to make a good visualisation.
For example I recently had the chance to collaborate with UNICEF to promote the release of The State of the World’s Children Report 2016. This data set is a gold mine with more than 246 KPIs at the country level on very different subjects like nutrition, health, HIV, and demography.
My first reaction was to apply my usual recipe. I asked which question I should answer with the visualisation, and I tried to reduce the scope to focus on one question. But my UNICEF contact explained that the goal of the visualisation was to promote the whole data set, which had required a lot of work to produce.
At first, I was lost. But I remembered two data visualizations I’d seen:
I also remembered situations during my career when an exploration viz was necessary:
- When a company executive wants a dashboard showing an overview of company activities
- When IT admins need to monitor their servers and applications activities
- When you need to give access to a large data set to a user who does not know how to use Tableau or any query tools
When we end up in similar situations, the risk is to build a visualisation that does not lead to any insight and instead confuses the viz user with too many filters and numbers. Even if you’re not answering a specific question, you need to help the reader. You need to drive him to insights. To do so, I have four recommendations:
- Define your KPIs wisely
- Use aggregation calculations with caution
- Keep it simple