The goal of data visualization is to convey information in an easily understood fashion and to make a point. Holistically, the entire data set should tell a story, and as follows, any visuals, be it a chart or infographic, has to tell that its piece of the story in a manner that is easily understandable and true to the data. On an individual level, charts should communicate key messages and be able to stand alone outside the context of the report.
Often, research firms and marketers will use their raw data to create the same charts one after another. While an efficient method of turning data into something visual, it leaves much to be desired. We know that visualizations help people retain more information, but when one sees 50 of the same chart in a row, all they are going to remember, if their brain has not melted from boredom, is that the presentation and report lasted an eternity. And if the same chart format was used over and over again there is always some question as to whether the graphs were generated correctly.
On the flip side some will focus intensely on the visual aspects of a chart, creating visually impressive data visuals that end up requiring intense review and deciphering to determine what they are trying to convey. Charts such as these can lead to misinterpretation of the data leading to false conclusions, and worse, bad and costly business decisions. Chartjunk, a term coined by Edward Tufte, an expert on informational graphics and professor at Yale, refers to visual elements in charts and graphs that are not necessary to comprehend the information represented and can distract the audience from the information. In his book,
Envisioning Information, he presents a chart on the average price of diamonds as an example of chartjunk.
In addition to displaying the data in a coherent manner, it is very important that data visuals do not distort the meaning. It is easy to skew data visuals in a manner that misrepresents what the data actually means. Charts and graphs can easily be manipulated to make a point that the data might not state. Even the U.S. Department of Education is guilty of this (although political motivations may be the reason behind this) as seen in the chart below.
Two things immediately jump out:
Using the same data, we can quickly develop a simple yet visually unappealing chart that shows while there is an upward trend, it is not nearly as impressive as the previous chart implies. In addition, we no longer have to worry about interpretation concerning how many percentage points a singular book is worth.
Lastly, the target audience must be considered. Different audiences, and in our case, clients, will have different preferences. Some may like simple and to the point data visuals while others expect more detail. Some may desire more visuals and a summary while others prefer just the summary.
As such, researchers, marketers and anyone tasked with reporting on data has to take multiple things into consideration when tackling any data set. However data ends up being visualized, it is most important that it remains accurate to the data and that it tells a cohesive story.
Xavier Alvarez is well versed in data visualization and was born in Mexico City, raised in Louisiana, educated as a Biomedical Engineer at Tulane University, living in San Diego, bilingual, frequent traveler to many places including Mexico, reluctantly classified as a Millennial, and is a Project Manager at Q2 Insights, a research and innovation consulting firm with offices in San Diego and New Orleans. He can be reached at (760) 230-2950 ext. 4 or email@example.com.
This entry was posted in Trends and tagged on September 7, 2016 by brett_adm