Web-Based Big Data Integration Visualisation Solutions

Abstract

Industries’ projects are associated with large amounts of data throughout the project lifecycle. As the size of the projects grows, so does the data associate with the projects. To generate useful information from Big Data, appropriate predictive analysis and data visualisation tools are required. Therefore, the use of visualisation techniques will target this expected evolution of big data. Thus, this study aims to give an overview of the migrations of an existing computer-based application, used to analyse multidata sources of enterprises, to a web-based application. Essential development aspects were concerned with the process of application development, platform development, software utilisation, and efficient display interface according to the enterprise’s requirement. Two solutions such as Microsoft Power Business Intelligence (BI) and the Dynamic Web System have been presented that proven to be widespread because these solutions have met the enterprises’ requirements in terms of expenses, policy, security, maintenance, and interactive interface. Also, an assessment of these solutions and challenges to adopting has been presented. Eventually, the system developed on the web overcomes computer-based systems in solving their problems such as deploying and maintaining applications and providing efficient and richer user interfaces for users. The web-based visualisation application has wide beneficial features; it provides high-performance real-time data analysis, data multimodal visualisation, and friendly to use. Web-based applications will increase confidence in decision-making based on data visualisation, which will positively reflect on comprehensive data analysis processes for project success.

Citation

Yousif, O.S. and Zakaria, R. (2022), "Web-Based Big Data Integration Visualisation Solutions", Din, M.F.M., Alias, N.E., Hussein, N. and Zaidi, N.S. (Ed.) Sustainability Management Strategies and Impact in Developing Countries (Community, Environment and Disaster Risk Management, Vol. 26), Emerald Publishing Limited, Leeds, pp. 103-117. https://doi.org/10.1108/S2040-726220220000026009