Literature Review of Data Visualization

    Data is explained in so many ways for the real understanding of data, and one of the methods to elaborate data is a data visualization. It is a fact that data can have different facts and figures, and the beauty of data visualization is that it can elaborate data with the help of different visual elements such as maps, graphs as well as charts. The good thing about this graphical representation is that it provides a nice view of data to understand its patterns, outliers, and trends. It has been observed that the use of graphical representation can be beneficial in so many ways because it helps others to look at some critical information with more interest (Healy, 2018)

            It is vital to understand why data visualization is an important tool to be used in various aspects while understanding or explaining data. It has been observed that it is easier and more convenient for a human brain to get the understanding of data with the help of graphs, maps as well as charts. There can be data, which may be complex to understand like when it is only looked in numbers, it may seem difficult to understand for humans, but when this data is elaborated with certain patterns and trends shown with graphical representation, then even the complex data can look an easy one to understand. The other great thing about data visualization is that it is not limited to any particular field, which means that it can be used by any field. The organizations with a large amount of data can take benefit by using data visualization for interpreting and representing data in a simple way (Sadiku, Shadare, Musa, & Akujuobi, 2016)

            It has been said that data visualization can be important for business organizations like they can use it in their performance management because it can certainly play a big part in it. A study was conducted in 2017 to see the role played by data visualization in performance management as well as for analytics. The study tried to analyze the important role of data visualization by elaborating data with different graphical representations so that data analytics has proceeded and performance management measures are analyzed. The study concluded that it is critical for accountants that they should incorporate data analytics so that they are able to make informed and well thought strategic decisions. The students were asked to use data visualization so that real data of customers as well as revenue data can be presented and elaborated. The overall study proved that students, as well as professionals, can take so much help from data visualization if it is used for elaborating data to make decisions regarding performance management (Kokina, Pachamanova, & Corbett, 2017)

            It has been mentioned earlier that data can be used in different fields of studies and it can serve different purposes. It was found that the use of data visualization is essential in explaining research articles so that readers can see graphical representation to understand data with more meaning. The use of data visualization is recommended in the range of topics covered by research articles (Schultz, 2018). It is also a fact that when scholarly information is presented and explained, it can have millions of data such as citations, authors as well as papers. Now, with digital publishing, the amount of data is growing with the passage of time. So representing such a large amount of data is becoming a big challenge. There could be various unseen and hidden patterns in the scientific data, and they cannot be understood and identified if the visualization of data is not done. So, the scientist can take benefits from data visualization to structure a large amount of scholarly information by structuring data with graphical representation. There may be many issues in doing so, but a successful effort will always prove the handful (LIU, TANG, WANG, XU, KONG, & XIA, 2018)

            It is important to understand for users that they can use different techniques to move forward with visualizing data, and one of the techniques is visualizing data with treemaps. In data visualization, the treemaps can be instrumental to elaborate data with more meaning, and information can be represented in an effective manner. It is important to know that there are different techniques of treemaps such as 3D Tree-maps, Cushion Tree-maps, Circular Tree-maps as well as original tree-maps. The users must understand that a variety of treemaps can be used to represent the range of data. One treemap may be useful in one situation, and it may not prove beneficial in explaining other kinds of data. So, it is up to users to select suitable treemap techniques to represent their data so that graphical representation comes with easy information to be understood by its audience. If data has a complex and large amount of tree structure, but it is represented with accurate treemaps, then it is always easy to elaborate and explain even complex and large amount of data (Long, Hui, Fook, & Wan Zainon, 2017)

            The users can use tree visualization of data in different aspects of elaborating a large amount of data. There are multiple tree visualization techniques are available, and each one should be chosen as per its suitability and compatibility with the available data, which is going to be represented. It is important to realize that data can be represented with not only multiple trees, but single as well as pairs of suitable trees. If data is large and it is having distinct structures, then it is advised to use multiple tree structures of data visualization. The overall review of literature has shown that data visualization is becoming a critical tool to understand and elaborate a large amount of data being generated on a daily basis. If data visualization is properly used by companies, they can get so many benefits from it to get real depth and understanding of their existing data, which can help them to notice viable trends and patterns to make informed decisions for their future strategy (Graham & Kennedy, 2010)

References of Data Visualization

Graham, M., & Kennedy, J. (2010). A Survey of Multiple Tree Visualisation. Information Visualization , 9 (4), 235-252.

Healy, K. (2018). Data Visualization: A Practical Introduction. Princeton University Press.

Kokina, J., Pachamanova, D., & Corbett, A. (2017). The role of data visualization and analytics in performance management: Guiding entrepreneurial growth decisions. J. of Acc. Ed. , 38, 50-62.

LIU, J., TANG, T., WANG, W., XU, B., KONG, X., & XIA, F. (2018). A Survey of Scholarly Data Visualization. IEEE Access , 6, 19205-19221.

Long, L. K., Hui, L. C., Fook, G. Y., & Wan Zainon, W. M. (2017). A Study on the Effectiveness of Tree-Maps as Tree Visualization Techniques. Procedia Computer Science , 124, 108-115.

Sadiku, M. N., Shadare, A. E., Musa, S. M., & Akujuobi, C. (2016). DATA VISUALIZATION. International Journal of Engineering Research and Advanced Technology , 2 (12).

Schultz, H. D. (2018). Visualizing data in research articles. The Journal of Physiology , 596 (16).