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# What is Data Visualization? - Definition & Examples

Instructor: Sharon Linde

Sharon has an Masters of Science in Mathematics and a Masters in Education

Data can sometimes be overwhelming, which is why a tool like data visualization can help it seem more manageable. This lesson goes over more specifically what data visualization is and how it is being used in today's business world.

## What is Data Visualization?

When many people look at data, they perceive just a sea of meaningless numbers. Data visualization is a trend that seeks to combat the natural reaction many people have to raw numbers. Take Gunnar, for example. He is dejected and perplexed. He has just come out of a corporate meeting where he had been trying to communicate what he thought was an important trend in the sales data to the company leaders. However, they had asked very few questions, and clearly didn't understand what he was trying to communicate. He isn't sure what went wrong.

Later that day, Gunnar talks to a colleague, David, about his experience. David is not surprised by the poor reception at the meeting. He explains that most people are not mathematically oriented like Gunnar and can't see trends in raw data. To get most people to understand what the data tells Gunnar, he will have to change the form of the data by making it more visual. Data visualization is a growing field in the business world that takes raw data and organizes it to tell a visual story. David explains there are many ways to do this, from simple tables to very expensive computer software services.

## Simple Example

Gunnar had originally shown his superiors this chart:

'City' '2014 Sales' '\$ Growth'
NY \$1,976,252 \$188,163
Chicago \$1,652,384 \$42,613
LA \$1,256,849 \$45,570
Charlottesville, VA \$357,961 \$40,075
Missoula, MT \$202,525 \$44,772
Iowa City, IA \$123,456 \$25,518

How does the chart work?

Gunnar is showing them that, although the large cities have shown the largest growth in terms of sales dollars, the largest growth percentages have been in smaller cities. Also, the largest potential for sustained growth is in the smaller cities as well - because there is much less competition for their products.

David suggests making some changes to improve the table:

1. Include fewer numbers - a maximum of 10 numbers on any one page.
2. Drop '2014 Sales' and '\$ Growth' columns.
3. Include '% Growth' and 'Competitors' columns.
4. Drop some of the cities to make fewer numbers possible.
5. Reorder the chart to reinforce the point about smaller cities.

The reworked chart now becomes:

'City' '% Growth 2014' 'Competitors'
Missoula, MT 22% 0
Iowa City, IA 21% 1
NY 10% 5
LA 4% 4
Chicago 3% 5

Gunnar is surprised, thinking this new chart doesn't really show any new information the old one didn't. David explains that although the chart may look the same to him, most people looking at the two charts see something completely different. The second chart drives home Gunnar's point, while the first one buries it in a sea of numbers.

## Other examples

As you can see with Gunnar's example, data visualization can start on a very small scale.

Other examples would be graphing trend lines for measurements that tend to be very erratic:

In the above picture, even though it is in another language, it's very easy to tell that there is a cyclical increase and decline (blue dots), but overall the moving average is increasing (pink dots).

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