The idea of Data Visualization isn’t new. Besides, it has been around for a considerable length of time. Data visualization refers to the techniques used to communicate data or information by encoding it as visual objects like points, lines, bars contained in graphics. Data visualization plays a key role in data science or data analysis. In this world governed by Big Data, data visualization enables you or the decision-maker of many enterprises or industries to look into analytics reports and understand concepts. An American computer scientist Ben Shneiderman expressed that “ Visualization gives you answers to questions you didn’t know you had.” Edward Tufte is a graphic design theorist and statistician that many consider the father of data visualization expressed that “ There are two goals when presenting data: convey your story and establish credibility.” In 1967, Jacques Bertin, published the Semiologie Graphique, considered the theoretical foundation of data visualization. Throughout history, they have been influential visualizations, but perhaps the biggest changes came with the development of computers.
We need Data Visualization in light of the fact that a visual rundown of data makes it simpler to recognize examples and patterns that glancing through a large number of columns on a spreadsheet. Information representation is firmly identified with data illustrations, data perception, and exploratory information investigation. In 1983, in the book “The Visual Display of Quantitative Information” Edward Tufte communicated that “Excellence in statistical graphics consists of complex ideas communicated with clarity, precision, and efficiency. Graphics reveal data. Indeed graphics can be more precise and revealing than conventional computations”. John Tukey and Edward Tufte pushed the bounds of information representation .Tukey once communicated that “ The greatest value of a picture is when it forces us to notice what we never expected to see.”
The possibility of representation information continued advancing after some time, and with the coming of PCs and fast development of innovations, the control certainly took a quantum jump forward. We live in an energizing yet testing time for information representation. As we enter the data age, it’s both energizing and startling to envision what’s in store available for us, both as people and as a general public. By consolidating data visualization best practices with current computerized innovation, numerous organizations that have an arrangement with gigantic measures of data can rapidly investigate it and get information driven bits of knowledge.