Data visualisation gives a clear idea of what the information means by giving it a visual context through maps or graphs. It is easy for human brain to comprehend thus making it easier to identify patterns, trends and outliers within large data sets.

Though data visualization use graphics and images to convey information,

Data visualization pioneer Ben Shneiderman says

“The purpose of visualisation is not pictures, but insight.”

That means turning data into charts far less useful than turning data into something meaningful in the mind of the audience. The brain devotes a large amount of its energy to visual processing.

Occipital lobe which is located at the back of the head, occupies some 20% of the brain’s overall capacity and is responsible for vision and being able to visualize

Researches say,

  • The human brain can process an image in just 13 milliseconds – (Source: MIT)
  • We are exposed to 5x more information today than we were in 1986 – (Source: Telegraph)
  • Human brains process visuals 60,000 times faster than they do text – (Source: University of Minnesota)

Most of the human brain is devoted to fast visual processing (touch 8%, hearing – 2%, Brain – 30% to 40%. The need for speed could tip the balance between life and death.

We need to detect, match and make sense of patterns, assign virtual attributes such as colours, shapes, translate data into visual code, find the right tools in your toolbox, clarify data for users.

Data visualization helps to adapt to data flooded world. The more you become aware of people’s visual processing strengths and limitations, the better your designs will become.

“Assemble elements to help people think clearly and accurately”


As a data visualisation designer, one needs to think about using design elements to help people both perceive and think about data.

Nobel Prize winning Psychologist “Daniel Kahneman” suggested 2 systems

  1. System 1: It involves more automatic and immediate perception such as noticing an unusual pattern of movement in the bushes. This is where visual encoding and things like Gestalt principles (you can refer my blog on Gestalt Principles )be touched.
  2. System 2: This is slower and more deliberate cognition. That is, thinking about the meaning of certain sensory cues. What interpretations and questions should arise from a particular visual pattern.

For example,

An analyst might immediately notice a single dot sitting alone but nearby to a cluster of other dots in a scatter plot – This is System 1

If the analyst spends few moments considering a bad data as meaningful outlier with further investigation – This is System 2

How do we know we are choosing the right visualisation? One of the challenge is actually being able to decide what is the best visualisation for the data type that one has. Knowing the intent or purpose of a particular visual and its advantages and disadvantages will help inform one’s decisions.

There are different visualization types to choose from namely Text or Number visualization, Table visualization, Heat Maps, Scatter plots, Line graphs, Bar graphs, Waterfall graphs, Maps, Pie Chart, Trellis plots, Stacked Area charts, Line graphs with totals above, stream graphs and many more..

“Act ethically while applying sound design principles”