Telling a Good Story Using Data Visualization Techniques
In the contemporary world of Big Data, the technique of visualizing large sets of data
involves a step-by-step process of presenting data mainly by encoding it using design elements
that provide accessible ways of understanding data patterns, outliers, and data trends. Therefore,
we can use data visualization elements to conduct thorough analysis of large sets of information
in order to make data-driven decisions. The fact that human culture is visual, data visualization
techniques utilizes visual arts such as maps, charts, and graphs to grab our attention and interest.
The technique is often a storytelling with a purpose. The graph below provides a clear story that
can be used as the perfect example of data visualization.
Source: (Martin, 2018)
In this sense, businesses often utilize the right visualization technique to read data and to
tell a story in a creative way by drawing conclusion about the set hypothesis, establishing
patterns and trends, and/or prove theories that can one way or another help an organization to
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establish data-driven decisions. Exploratory and Explanatory data visualization techniques are,
however, crucial in analyzing data.
Exploratory Data Visualization
Exploratory data visualization (EDV) techniques use qualitative designs to convey crucial
information about an unknown set of data. Variables within the model can be refine and defined
using exploratory techniques because appropriate data analytics tools are often utilized by
researchers to emphasize a certain figure or develop suggestive ideologies from an unknown set
of data to bring out clear information. Furthermore, the complexion of storytelling tends to be
enhanced using exploratory data visualization technique as it defines and redefines significant
variables that are crucial to businesses. That is why organizations utilize EDV storytelling
techniques to pinpoint anomalous outliers, trends, including other essential aspects of data sets
that tend to clarify and establish the valuation of businesses operations. Besides, the fact that the
research goals of EDV techniques rely on graphical techniques, organization are expected to
assess the right chart, graph, or map in order to visualize data in a more professional way. For
instance, a simple histogram below can be used by researchers to examine redistribution
channels.
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Source: Source: (Yu, 2015)
As depicted in the graph, exploratory technique can be utilized by researchers to tell a
story of normality and non-normality probability plots. Here, a normal probability plot would be
demonstrated using a straight line whereas any other form of deviation, crooked line for instance,
would suggest non-normality in a given set of data.
Explanatory Data Visualization Techniques
We use exploratory data visualization analysis to convey substantial information of a
known set of data. During data analysis processes, explanatory data visualization technique is
often integrated with infographic elements in order to simply visual data during the presentation
phase and to enhance an individual’s ability to gain insights of trends and patterns that are
depicted on a given set of dat. Furthermore, with the integration of graphical elements that
express data attributes together with other infographic elements, readers can clearly gain insight
of an interactive story behind the elements and to make data-driven decision within a set of data.
Whilst the key findings may contain several, yet different dimensions of data analysis
processes, they tend to facilitate other processes of manipulating the displayed variables.
Therefore, it is through explanatory data visualization techniques that most of storytelling
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functions are linked with data depending on how they are structured. The chart below can be
used as the perfect example of explanatory data visualization
Source: (Murray, 2019)
While using the above chart as an example, readers can utilize explanatory data
visualization technique to understand how arctic has been declining since 1978. In short, the fact
that the chart tells a good story, the technique here will be used to capture the main idea through
bridging the gap between sophisticated design and beautiful story by combining the original
findings with other substantial research studies. Furthermore, the explanatory features can be
read and comprehended easily, and readers can quickly draw crucial ideas from the story in order
to make sound decision. Besides, with the use of the above chart as an example, readers can
affirm that the line chats are the visual patterns used to tell a story for decades while annotations
present in the line charts were used to convey substantial information to the readers.
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References
Martin, N. 2018. Data visualization: How to tell a story with data.
Forbes. https://www.forbes.com/sites/nicolemartin1/2018/11/01/data-visualization-how-
to-tell-a-story-with-data/#30b9396f4368
Murray, E., 2019. How Do You Tell A Story With Data Visualization? Forbes.
https://www.forbes.com/sites/evamurray/2019/02/06/how-do-you-tell-a-story-with-data-
visualization/#7d67106b4b58
Yu, C.H., and Ds, P., 2015. Exploratory data