Big Data Visualization Techniques for Decision Support Systems

Abstract

Big Data is defined as data that is growing in volume and form due to technological advancements and time. This rise will result in more complicated and unpredictable circumstances that will be challenging to appropriately assess and handle. Different kinds of information are sent via a network comprising connected devices. There are several uses for this information. Real-time processing of information and autonomous capacity for decision-making provide a substantial barrier to the continuous evolution of complex metropolitan infrastructures. For this reason, we provide a big data visualization-based paradigm for smart cities in this study. Big Data visualisation and Artificial Intelligence (AI) are currently being implemented in m-health to create an efficient system for healthcare. In order to gather data, 15 in-depth interviews with advertising and analytics executives in the United States and Europe who were involved in the Big Data Visualization (BDV) application were conducted. This was followed up by a questionnaire survey of 298 middle-level professionals in the US who work in marketing and analytics. The outcomes of the poll corroborate the theory that senior management is responsible for spearheading BDV sense making, which consists of four main activities: acquiring external knowledge, enhancing the quality of digitized data, experimenting with big data visualization, and disseminating information about big data visualization. Top management increases the impact of BDV competent people and facilitates sense making in order to accelerate progress towards data-driven decision making. According to this research, although the marketing department's access to higher-quality resources is enhanced by a move toward enterprise analytics, this strategy may impede the development of superior marketing understanding from BDV.