The Why of Data Visualization in Analytics – Can we do without Data Visualization?
The CEO of one popular company had proclaimed that executives today are like children; they like to see their reports in the form of pictures. A picture is after all worth a thousand words! Satire apart, as per recent research, the brain comprehends creative work the best when it is tired. That is to say, the brain thinks and perceives through its right half more clearly when the left half has switched-off! No doubt that even Archimedes was using his right brain when he came up with the framework about his Archimedes principle in a bath tub!! The popularly acclaimed “eureka eureka” moment happened when his left brain had almost dozed off!! Data Scientists have also observed this phenomenon vividly while studying huge amounts of data or Big Data and trying to come up with meaningful reports and crisp dashboards that are intelligible. They have now been using the concept of Data Visualization in Analytics that appeals more to the right brain for easy comprehension even when the left hemisphere of the brain is overworked!
What is Data Visualization?
By definition, Data Visualization is the visual communication of information that has been abstracted in some schematic form. Data Visualization is a feature incorporated in Business Analytics for enabling executives to better understand the reports that are extracted out of tons of data by building a visual context around it. To put simply, Data Visualization tends to make complicated data accessible, intelligible, and usable.
Importance of Data Visualization:
As stated by Micheal Dell, Big Data Analytics is the next trillion dollar market as most organizations have to manage huge amounts of data. Hence they need tools to not only analyze it but also churn graphical dashboard summaries for quick analysis. Scrolling through table-based summaries derived from Big Data can cause an information overload. This is precisely the stage where Data Visualization steps in and makes the information more comprehensible through the diagrammatic shapes, sizes, and thickness and thinness of lines. The graphic nature of the dashboards and reports enables businesses to act on the data quickly as compared to table-based reports – the ‘analytics part’ and the ‘visualization part’ actually go hand-in-hand.
The data-to-intelligence journey gets complete only with Data Visualization. Visual sense is the most acute of the five senses. As per research, human beings grasp the differences in colors, hues, length, width, shape orientation readily without much effort. Hence communicating complicated data set in an intuitive manner becomes easy with Data Visualization.
The feature of Data Visualization clearly brings forth the patterns and correlations that may be deeply buried in data and may be unnoticeable in table-based reports. The images and charts also include ‘interactive capability’, which enables the executive to drill-down into the analytics tables for deeper analysis.
Today, BI Analytics tools have also made it possible to leverage current IT investment, streamline existing data in any data source, and use plug-and-play interfaces to derive colorful dashboards. Tableau, Netezza, nSights, and Cognos are some of the products that are making headways in the market.
Now, it is also possible to host the BI Analytics and Data Visualization framework on Mobility platform. The arrangement not only allows executives to generate crisp and colorful dashboards at the click of a button but also tap deeper into their business intelligence while on the go on their handheld devices.
Data Visualization is indispensable especially when it comes to Analytics of Big Data. However, Data Visualization alone does not produce any valuable insights of its own – it is the role of analytics. Data Visualization just summarizes and conveys the analytics, which are produced, in a pictorial summary with added features for drill-down. To make the journey of Data Analytics and Data Visualization more effective, efforts have to be taken on ‘how the data is collected’ and ‘what data is collected’. In absence of which executives may tend to waste time in just analyzing and finding meaning in their existing data in different ways without really getting to the bigger picture. Thus a meaningful dataset, Data Analytics, and Data Visualization have to work together in order to gain quick actionable insights even through Big Data. Only then the executive can relate to the ‘big picture’ and take informed actions.
– Vikram Kole
Datamatics Global Services Limited