Emerging Trends of Big Data Applications in Libraries: An Overview

In a constantly changing environment, educational institutions, libraries, and books have their own record-keeping and administration methods, making obtaining data from a single, central source challenging. Large volumes of big data have been produced due to library digitization. Still, this abundance has made it more difficult for academics, researchers, educators, and policymakers to increase the calibre and effectiveness of their work. Delivering books and articles that suit customers’ preferences has become extremely difficult. To lessen the time it takes to find and access pertinent reading material, this study suggests a system that gathers and combines data from multiple sources and organizations in real time. Reducing the time between finding and consuming content is the primary goal. Bridging this gap is crucial since information access can be expensive, especially for those with restricted internet availability. This research aims to create a technique that drastically reduces the time needed to find relevant reading material, in line with the principles of contemporary recommendation systems. The technology efficiently examines book descriptions and metadata to find content that matches users’ interests. It gathers vast data from academics, researchers, educators, and policymakers. The algorithms that can partially automate specific jobs are trained using this big data. Therefore, the insights gained from analyzing this extensive, integrated library data can significantly improve information access. This development not only makes it easier and less expensive for researchers, academics, and decision-makers to acquire the resources they need, but it also increases the accessibility of information for marginalized and underprivileged populations.