An advanced data virtualization architecture for improving decision-making efficiency in Business Intelligence

Abstract

This paper discusses a new architecture for Data Virtualization (DV) that aims to improve current practices in Business Intelligence (BI). The integration of AI for optimizing queries, blockchain technology for security and transparency, Edge computing for closer to source data processing, and an ergonomically designed interface for better usability all work together to improve system flexibility, performance, and scalability. Following a review of literature and expert interviews, the study formulated eight major modifications: two at the User Data Visualization layer, two at the Data Access and Distribution layer, and four fundamental modifications throughout the complete system. The proposed refinements help in merging the data in real time, decrease the lag time, and increase responsiveness to data. With the new DV architecture, businesses are not only able to seamlessly integrate and analyze data, but they are also able to digitally transform and gain operational efficiency and a competitive edge. Organizations can continuously revise their strategies with the help of this architecture and achieve sustainable development in a fast-paced global marketplace