Data Visualization is an important concept while working with a large number of datasets, finding insights and presenting those insights in an appealing way. Every data in visual form has some story to tell if presented in the right form reaches to its user with a clear message, which otherwise could become ambiguous.
Data Visualization on a given data could influence the user and could catch his attention while at the same time could also distract him as well. Imagine a data of the senior age groups living with their family in a city presented with the help of a pie chart. If the visual is presented in a way that it creates ambiguity to the user who is analyzing it, would it make any sense?
Obviously, it is a little boring to work at data sets containing only figures and your audience will always go for a Data Visualization while you present your data. But what when you do a lot of work with your data and finally present it before your audiences and your audience do find it meaningful? It becomes a clear waste of time indeed.
I have come up with this article to make you aware of some of the points that will make the Visualization of your Data appealing and more audience understandable.
Let's have a quick understanding of these:
- Make your Visualization Simple
Its a belief of most of the people that complex visuals provide justification to their Data Visualization and make them more appealing, which is seriously not the case. Whenever you are doing Visualization of your data, try to make it simple so that your audience will understand your data at first glance only. Not everyone wants to think much. Put things simple and understandable. Try to think from everyone's perspective.
Always make a good choice of the colors that you put into your Visualization. Don't try to put colors which make your data distracting. It matters. Colors have an effect on the mind. There are colors which are never preferred while presenting data.
The motto behind creating visuals of your data is to provide your audience with useful information and your findings. Do not forget this. Do not fade your data and insights with the visuals. Go for the simple background but an effective one to interpret your data.
Always try to understand which visual will best express your data rather opting for any anonymously. Think about your findings and accordingly find the right visual justifying it.
- Do not overflow your visual with data
Do not try to put many insights into one visual creating it hard to understand by your audience. Maintain a balance so that each of your useful findings reaches to the audience and at the same time the visual not looking like a flood of information flowing into one picture.