HCI 660 How is data visualization used?
The Utilization of Data Visualization
Data visualization refers to the practice of changing big data sets and metrics into visuals such as graphs and charts. The resulting visual representation of data fosters easy recognition and sharing of instantaneous trends and insights of the information embodied in the data (Stadler et al., 2016). Data visualization integrates aesthetically pleasant and user-friendly features that make research and data analysis quick. Data visualization is also a great communication tool (Healy, 2018). Data visualization can be used in health care to simplify patient care data, which is essential in helping nurses to analyze data and effortlessly leverage required information. Hospitals can also use it to enhance and better understand their operational costs, customer satisfaction, effectiveness, and trail patients’ progress (Healy, 2018). Examples of data visualization in hospitals include bar graphs depicting patient satisfaction ratings, line graphs showing operations and staffing trends, and pie charts showing health care effectiveness.
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Organizations can use different approaches to determine the best way to present data. The first consideration is summarization. Often, the use of long texts is confusing and tiring. The organization needs to summarize its data and present the outcomes in a consolidated way that helps readers get the impression of the essential findings without going through the entire manuscript (Nieminen, 2020). The best way to summarize the findings is through visual forms such as pie charts, tables, and line graphs. The other consideration is clarity. Some information is better understood when illustrated visually. Therefore, the organization should consider organizing the information in tables or graphs to enhance clarity. The other point of determination is whether the data representation enhances comparison (Nieminen, 2020). The organization needs to consider using tables, diagrams, and graphics to expose the distinctions between different subjects or parameters in question.
Healy, K. (2018). Data visualization: a practical introduction. Princeton University Press.
Nieminen, P. (2020). Ten points for high-quality statistical reporting and data presentation. Applied Sciences, 10(11), 3885. https://doi.org/10.3390/app10113885
Stadler, J. G., Donlon, K., Siewert, J. D., Franken, T., & Lewis, N. E. (2016). Improving the efficiency and ease of healthcare analysis through the use of data visualization dashboards. Big data, 4(2), 129-135. https://doi.org/10.1089/big.2015.0059