Every image tells a story — Data Visualisation
Tags: Data Driven Decisions, Data, Data Driven, Data Visualization

Data age — In a war of Verbalisation (To remember using words) vs Visualisation (To remember using Images/Pictures). Visualisation seems to be an emerging winner with clear advantage of how human brain process information. Human brain understand and recall information better when visualised.

Incessant bombarding of information and decreasing attention span makes it more difficult for human brain to retain verbalised information for long time in modern world. Thus, arise the need to make an impact using human visual abilities to convey the business message.

What is data Visualisation ?

New technological innovations have made it easier to process large volumes of data and visualisation sits at the heart of Business Analytics tools.

Simply put, data visualisation is using pictures to represent data. Data visualisation turns numbers and letters into aesthetically beautiful visuals.

This visuals further helps –

To identify and/or spot any patterns, exceptions quicker.

To communicate insights clearly

To display data to highlight cause and effect.

Components of Data Visualisation

What’s the business context(Question)?

Who is the audience of the data visualisation story?

Does data match and support the story?

How to visualise and build the story?

Customer is the king in business world and context is the king in Visualisation world. Without the business context, all of the gathered data is useless and vice versa.

Next step is to build a meaningful and engaging story -

The story so good that it has the potential to captivate audience.

The story so good that it leads an audience to desired destination.

Edward Tufte — The Leonardo Da Vinci of data visualisation, an Author and Visualisation Expert’s summarised checklist for effective data visualisation.

1. Above all else show the data — Let the data speak.

Design Transparency- Keep the focus on context and not the visualisation technique.

Avoid distortion of facts revealed by data.

2. Maximise Data-Ink Ratio — Tufte defines the data-ink ratio as the amount of data-ink divided by the total ink required to print the graphic.

Display as much data as possible using as little ink as possible.

Avoid using ink on elements of visualisation not associated with data.

3. Chartjunk — Unnecessary visual elements in visualisation content that distracts audience from information. Less is more.

Avoid too much visual art — Excessive shading or patterning of chart features.

Non-data creative graphics — pretty visualisation with lot of color schemes and patterns can detract from the actual information content.

4. Information Layers

Layering is using colour, different design elements (Typefaces, Font styles) to organize the visual display of information a little bit better, this give hints of the different categories.

Multiples — Maintain a consistent design to highlight data, changes in design can distract from data changes.

Color — Rainbow is not a choice here(😝), colours can be useful or harmful in conveying a message. So, use wisely.

5. Annotation

Label where necessary and let it stand out from data.

Images still need identification/labels.

In the end it is about presentation of Insights to the right people at the right time, in easy-to-remember formats.

Simple design, intense content — Edward Tufte