Interactive Visualization for Statistical Modelling through a Shiny App in R

The importance of analytics and visualization tools has been growing over the last decades to handle big data which steamed from all aspects of life. The focus of this paper was on visualization as a crucial tool in presenting complex raw data and modelling results to provide easy-to-understand actionable information that facilitate decision-making. However, limited research distinguished between “data visualization” and “model visualization”, which has been clearly made in this paper. Furthermore, this paper aimed to shed light on the importance of interactive visualizations to compliment statistical data modelling using R and Shiny for its advanced capabilities. Specifically, a methodology has been proposed based on a hybrid development lifecycle that adopts the Agile Software Development Lifecycle and the Data Analytics Lifecycle. Finally, by presenting a case study to model the dynamics of COVID-19, it was found that R and Shiny alongside the proposed hybrid development lifecycle significantly reduced the amount of time required to build visually interactive applications. The reported results highlighted the effectiveness of the adopted approach in assisting and guiding researchers and developers in building interactive applications that leverage Big Data Analytics.