What is my
definition of data visualization? My definition of it is using visual aids such
as graphs and maps to make important actionable insights easily comprehended by
target audience. Given this day and age, target audience have very short
attention span and to be able to squeeze so much information within such a
short span gets more challenging as we go by. Thus it is important that data
scientist also understand the importance of visualization and also the know the
pros and cons of each visual aids.
Many a
times, data visualization are sold as visual analytics but both of them should be totally different in my opinion. Data visualization is much more closer to descriptive statistics (where things have happened) whereas if you look at the definition of just 'analytics' alone, besides
descriptive it should also contain predictive component as well. So visual
analytics should be using visual methods to make certain predictions (at least
this is my opinion for it to be call "Visual Analytics"). While doing
research for this blog post, I came across the definition of Visual Analytics
in Wikipedia but alas, it would take a few hours for me to digest its
definition. Hopefully someone can go through it and come up with a simpler
definition.
And also
there are some cognitive blind spots when we use visual aids to present
information as compared to predictive statistical models. If I plot the
outbreak of a disease on a map over time, and it seems to move from east to the
centre, our brain would start to link the points up, extrapolate , coming to a
conclusion that the disease will continue to move through the centre of the map
towards the west side. Really? Do you have data to support that the disease
outbreak may not 'suddenly' appear at the west side of the map and move towards
the centre? This is not true in statistical model because through the
statistical models, we are very sure the independent variables would predict the
outcome with a higher probability based on training data as compared to the
simple 'extrapolation' on visual aids.
Now I am
not saying that Data Visualization is not important. It is
definitely important. After generating so much insights from data, the very
last step is to share the insights so buy-in can be gained and actions can be
taken to generate value from Analytics done. If at this stage, there is no planning of the
visual aids to show the actionable insights, it would be like a striker that has the ball with him in
front of a goalkeeper-less goal post and fail to score. ALL efforts wasted.
So what are
the resource available to learn more about
visualization? Well, there are two Masters on Visualization, namely
Edward Tufte and Stephen Few.
Their
websites are as follows:
Stephen
Few: http://www.perceptualedge.com/
Edward
Tufte: http://www.edwardtufte.com/tufte/
Their
books:
Stephen Few
Edward Tufte
Have fun learning about Data Visualization in your Data Science Journey!
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