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Data Visualization: The Art of Building A Picture Story Around Data

The origin of the popular saying, ‘A picture is worth a thousand words’ is debatable. However, its message that a single visual illustration can convey a more crisp and clear information about something than a description in a thousand words, is indisputable.

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According to a research study conducted at the 3M Corporation, humans process a visual 60000 times faster than a text [1]. Further studies have shown that the human brain construes a text in a linear, sequential manner while it can perceive the elements of an image simultaneously. Thus, the understanding about a topic is likely to be faster and more comprehensive using graphical illustrations than just words.

In fact, as I write this piece of article, my attention is drawn to my two-year-old who is looking at his picture books carefully with interest but how he does not like to even leave through the textbooks of his elder brother. It makes me realize that the earliest learning for the tiny humans starts by observing colorful toys and objects, and looking at picture books due to their easier interpretation. The human brains have the innate capacity of distinguishing between various colors and distinct shapes and deciphering patterns just by looking at them. In fact, in a lifetime majority of communications for humans are non-verbal and most of the information processed by the human brain is in the visual form. This capability is also used to understand and make sense out of the plethora of data by translating it into visuals form via the art of data visualization.

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Data visualization refers to the graphical representation of the data. If the data is provided in the form of a spreadsheet or a text, it is usually difficult to draw conclusions as to how the different elements in the dataset relate or to infer the trends. However, if you are able to produce an illustration or a diagram representing the data, it makes it easier to interpret it. By looking at the visualized data, it is possible to identify the trends or outliers or correlations or patterns. Simply put, data visualization allows to better see, represent, and interact with the data. This aids in the better analysis of the data and data-based decision making. In addition, it also provides an easy way to present the data and provide a visual story to the non-technical audience in a shorter frame of time in a more comprehendible manner.

Nevertheless, data visualization should not be confused with just putting data into a visualization tool to make certain figures. It is crucial to exclude any noise in the data without loosing any useful information during the visualization step in order to avoid any misrepresentation. Thus, data visualization is an art of building a meaningful picture story with data so that it is easier to understand, interpret, and identify any useful trends and patterns. For an effective storytelling, it is essential that the data and visuals are in agreement.

As mentioned above, the advantages of data visualization can be summarized in the following key points:

  • Better internalization of information

  • Visualization of patterns and trends

  • Interactive exploration

  • Enhanced information sharing experience

  • Effective analysis and storytelling

However, like any other methodology, data visualization also has some disadvantages [2] which are as follows:

  • Correlations maybe confused for causations

  • Use of an incorrect visualization can lead to biased or incorrect interpretation and loss of information

Therefore, it is important to choose the correct form of visualization to represent data and perform analysis. The visualizations can be classified into the following general classes:

  • Chart: It is a pictorial representation of a graph. It may be in the form of a table or graph or map

  • Table: The data is presented in a tabular form along the rows and columns

  • Graph: A diagram in which data is presented as either points, lines, curves, or area and is displayed along two or three (dual) axes

  • Geospatial: It is used to show data in a map form to show relationship or distribution of data and specific geographical locations

  • Infographic: In this type of visualization, we use both visuals and text to represent the data

  • Dashboards: In this, several visualizations are displayed together for easier way to present related data and results of its analysis

There are several visualization tools available with a graphical user interface that can be easily learned and used for the illustration of the data. Data visualization is applied in almost every field including but not limited to financial sector, retail sector, research, and healthcare.

I would like to conclude by saying that data visualization provides an efficient and effective way to represent data that makes easier to analyze and interpret.


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Bushra Singh
Bushra Singh

Great Insight! I totally agree with the point in this article. Good job in summarizing and establishing your point.

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