A Brilliantly Brief History of Data Visualization

A whirlwind tour of some of the key points in time and pioneers in converting statistics into impactful visualizations.

A Brilliantly Brief History of Data Visualization

Data visualization is a fundamental part of how people learn and comprehend things. Today's business intelligence (BI) and analytics systems have a large capacity for it as well.

So, how was data visualization created in the beginning? An interesting chronology has been created as a result of the modest beginnings and slow progress of data visualization. This blog is an introduction to the intriguing history of data visualization, which ranges from prehistoric cave drawings depicting the success of a hunt to sophisticated dashboards supported by the computer revolution.

An Introduction to Data Visualization History

Information was once inscribed into stones by humans. But as time passed, innovations like the compass and sextant produced exact measurements and accurate maps.

In the present day, data visualization is incorporated into BI dashboards to assist report developers in communicating the profound meaning behind metrics and figures and to graphically tell amazing stories that have never before been seen in recorded history.

Presentations and visualizations are the two main types of visual data representations. Both are crucial for producing stunning visualizations. Nevertheless, they all have requirements that must be fulfilled.

Presentation: to convey information visually. This visual depiction works best when there is a presenter and an audience.

Visualization: is a relatively recent idea, and its purpose is to encourage visual thinking. By posing questions and collecting responses from the audience, this interactive experience encourages participation.

Professionals are expected to use vast amounts of data to make data-driven judgments. We anticipate more development in data visualization in this context. Information visualization aids in making critical facts easy to understand and lets humans express their creativity, which is ultimately their greatest asset.

Data Visualization Chronology

Let us now take you on a brief historical tour of data visualization. We'll talk about the following historical eras:

  • Pre-Historic Data Visualization
  • 366-335 BC Roman Maps
  • 950-1092 AD Celestial Bodies
  • 17th Century Michael Florent Van Langren
  • 18th Century William Playfair
  • 19th Century John Snow
  • 20th Century Advancements
  • The Information Age

Pre-Historic Data Visualization

The earliest graphical representations were more likely made by scratching on rocks and drawing in the sand. The renowned Lascaux cave paintings, which date back 40,000 years, are thought by experts to have served as directions to the spirit realm and hunting maps. These pictures were probably depictions of the constellations from astronomy.

It is also evident from the early Babylonian world map about 600 BC that early civilizations first sketched on clay. However, other ancient civilizations, including the Egyptians, Chinese, and Greeks, also created maps to help in navigation. They were also employed in the creation of crop planting strategies.

366-335 BC Roman Maps

The Romans were renowned mapmakers because they wanted to efficiently control trade and the movement of the army. It displays the empire's transportation network from Britain to India.

The routes were shown as lines while the destinations were displayed as icons. The map resembles a schematic diagram, such as the one created by Henry Beck in 1931 for the London Underground map.

950-1092 AD Celestial Bodies

800 years before the first planned graphics were on the scene, in Europe. A remarkable figure was found that uses a grid approach to show the position and timing of planetary bodies.

However, it is almost impossible to determine the exact meaning. On the right side, planetary locations and trajectories were displayed, while timeframes were displayed on the horizontal grid.

Celestial beings were also projected during the Chinese Song Dynasty utilising novel methods that had not yet reached Europe by the sixteenth century. They created some incredibly complex star projections. However, this Chinese chart was preceded by the European chart that was previously presented.

17th Century Michael Florent Van Langren

The Flemish astronomer Michael Florent Van Langren is credited with coming up with the concept of presenting statistical information as a graphical representation in 1644. A single-dimensional line graph was used.

Van could have presented the information in tabular form, but he chose to use the graph and chart to show the vast discrepancies in estimations.

18th Century William Playfair

William Playfair, a Scottish political economist and engineer, is credited with creating statistical graphics. He released a book in 1786 that included data visualizations in the form of graphs. In his work Commercial and Political Atlas, he provided numerous graphs and charts.

Graphs were used throughout the text to show the English trade balance. You might be surprised to learn that several modern data visualizations employed by Playfair are still in use. However, it is important to note that during those times, data was typically presented in sterile tables without taking into account its potential interpretation.

19th Century John Snow

British physician John Snow used statistical data-based graphics to combat the cholera pandemic in 1855. He marked each cholera case with a dot on the map of London. These connections connected to a water pump on Broad Street, the site of the cholera epidemic.

These dots indicated that the majority of instances could be linked to a Broad Street pump. The subsequent research established a connection between cholera cases and the Broad Street pump. The map that Snow used fits the presenting style as well.

20th Century Advancements

By the middle of the 20th century, statistical graphics were extremely popular. The increased use of statistics, however, also gave rise to their use for unfair advantage. Because of this, an American author named Darrel Huff had to create the book How to Lie with Statistics in 1955 to draw attention to the abuse.

Ten years later, he also released another book, Semiology of Graphics, written by French thinker Jacques Bertin. Bertin's interest was piqued by a statistical mapping. He saw that the three different sorts of chart markers used in data views were lines, points, and regions.

The Information Age

After the invention of computers, data visualization advanced to unprecedented levels. In 1981, the first commercial graphical user interface was seen by humans. Spreadsheets drastically altered the format of information visualization, among other aspects. Without using any human effort, they created visuals and charts from information tables, such as scatter plots and pie charts. Essentially, they made it possible to visualise data using pre-made graphs and charts, which sped up and simplified the process.

With just a few clicks, anything may be drawn. Unlike before, when people would spend hours perfecting their drawings. The spreadsheet application also had functions for updating, formatting, and editing. A number of enterprise data visualization software options quickly entered the industry, bringing with them fresh charting methods and fashions.

21st Century Business Intelligence (BI) Dashboards

BI dashboards are reporting solutions that make it simple for users within an organisation to understand and work with data. Organizations can use it to find insights and find answers to various problems so they can make data-driven decisions. In other words, it displays important measurements and KPIs on a single screen. Because of this, several businesses are turning more and more to BI dashboards to help them make decisions.

Are you curious as to why businesses favour BI dashboards? It promotes a data-driven culture at all levels of an organisation, first and foremost. Additionally, it conveys how a company performs in relation to set objectives. Not to add that corporations always prefer to visualise complex relationships in a straightforward manner.


We hope you enjoyed reading our brief (but brilliant) history of Data Visualization. Although it feels that data visualization is still somewhat in it's infancy, it's certainly come a long way since pre-historic times.