{"id":6782,"date":"2018-11-20T06:00:51","date_gmt":"2018-11-20T06:00:51","guid":{"rendered":"https:\/\/www.anychart.com\/blog\/?p=6782"},"modified":"2018-11-20T06:18:06","modified_gmt":"2018-11-20T06:18:06","slug":"data-visualization-definition-history-examples","status":"publish","type":"post","link":"https:\/\/www.anychart.com\/blog\/2018\/11\/20\/data-visualization-definition-history-examples\/","title":{"rendered":"What Is Data Visualization? Definition, History, and Examples"},"content":{"rendered":"

\"Data<\/a>Data visualization<\/strong> is the practice of converting data from raw figures into a graphical representation such as graphs, maps, charts, and complex dashboards. Let\u2019s see what makes it important (meaning), how it has developed (history), and exactly how it can work in real life (examples). Join us on Data Visualization 101, an introduction to dataviz and its power.<\/p>\n

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Significance of Data Visualization<\/h2>\n

To understand how meaningful data visualization is, here\u2019s a simple fact: Human brains have a much harder time understanding complex data when it is encoded in numbers and text compared to graphics. Dataviz techniques take advantage of that quality, helping to present massive amounts of information in the most efficient, visual form.<\/p>\n

In fact, visually displayed data is easier to grasp and analyze, making it faster for decision makers to find patterns, including new and hidden, and to understand even difficult concepts. Charts, graphs, maps, dashboards \u2014 data visualization can be helpful in identifying issues and deficits, choosing the best product and business operation strategy, forecasting sales volume and stock prices, fine-tuning project management and resource administration, and so on and so forth.<\/p>\n

History of Data Visualization<\/h2>\n

\"ExampleThe concept of data visualization is not new. Moreover, it has been around for centuries. The earliest and most obvious examples of dataviz projects are maps. Then you have the pie chart which first showed up in the early 19th century. A few decades later, Charles Joseph Minard used statistical graphs in order to map Napoleon Bonaparte\u2019s Russian campaign of 1812, combining multiple metrics: the number of troops, temperature, distance, directions, and more.<\/p>\n

Other notable milestones in the history of data visualization include but are not limited to works of Nicole Oresme, Joseph Priestly, and William Playfair. All of them greatly contributed to the dataviz progress. Oresme was one of the greatest thinkers of the Middle Ages, and it could be said that he invented bar charts<\/a> in the 14th century, although it was Playfair who later gave the bar chart the form we know today. Priestley, in his chart of biography, used a timeline with bars to compare multiple persons\u2019 life spans. Playfair is also credited with the first use of area charts<\/a>.<\/p>\n

To learn more about the data visualization history, explore the biggest known milestones<\/a> Michael Friendly and Daniel J. Denis from York University featured in their book \u201cMilestones in the History of Thematic Cartography, Statistical Graphics, and Data Visualization: An Illustrated Chronology of Innovations.\u201d<\/p>\n

The idea of visualizing data kept evolving over time, and with the advent of computers and rapid growth of technologies, the discipline definitely took a quantum leap forward. Nowadays, even massive amounts of data \u2014 and big data itself \u2014 can be processed by dataviz software at a very high speed, opening up new exciting opportunities in the field of data analytics and business intelligence.<\/p>\n

Data Visualization Approaches and Examples<\/h2>\n

Visualization is ultimately a great way to let your data speak.<\/p>\n

Over the course of time, a variety of data visualization techniques have emerged, opening up opportunities to solve literally any dataviz task. Depending on what data you have to explore (or explain) and what analytical questions you want it to answer, you can pick one approach or another.<\/p>\n

With dozens of chart types available, each known to suit one particular purpose or another, it is extremely important to choose the right chart type<\/a>. In fact, picking a wrong form is one of the most common \u2014 and critical\u00a0\u2014 visualization mistakes<\/a>.<\/p>\n

Let\u2019s look at seven common examples of data visualization tasks and see what chart types are typically the best fits. Click the corresponding links to learn more and check out interactive chart examples.<\/p>\n

1. Compare Data<\/h3>\n

\"Column<\/p>\n

To compare data<\/a>, the following chart types are commonly helpful:<\/p>\n