🏆Data Viz Best Practices
Think of children’s story books, what catches your attention (or used to)? Now think of a data visual (tableau, Power BI, D3.js, etc.), would you expect a similar level of excitement and curiosity? I personally can draw similarities between the two. Creativity is one to begin with. And each of the following is probably a separate topic by itself:
- Color – is the first aspect of any visual that you interact with. It drives the emotion of the data and the idea is to keep it in line with the tone of data story you are telling. Eva Murray, a Tableau Zen Master, summarizes this in her article and there is no better way to put it.
- Titles – the right title for a visual is as important as is choosing the way to represent the data. In a professional setting, consistency of title’s font and color play an important role as well. Sometimes it helpful to follow company templates.
- Simplicity – it’s tempting to use the most intriguing and complex visuals but, in my experience, it’s becomes crucial to step back and let the data drive the visual and not my creative obscurity. 🙂
- ACD – annotate, connote, denote – specifying events and explaining why trends might be the way they are, is prime. From an audience perspective, it’s unlikely for everyone on have the same level of familiarity with the data set.
- Explore – simplicity should not limit the appetite to explore and experiment with the different ways of adding to the dataset. I have learned to augment my dataset with open data and sometimes that can make your data story stand out.
With a data story it is most important to articulate the analysis, findings the right way. The goal should be to trigger a response, not a reaction.
By: Anshul Mittal
Image Source: https://www.pinterest.com/pin/127719339402947726/