Emerging Trends of Big Data Applications in Libraries: An Overview

In a constantly changing environment, educational institutions, libraries, and books all have their own record-keeping and administration methods, making it challenging to obtain data from a single, central source. Large volumes of big data have been produced as a result of library digitisation, but this abundance has made it more difficult for academics, researchers, educators, and policymakers to improve the quality and effectiveness of their work. Delivering books and articles that suit customers’ preferences has consequently become extremely difficult. In order to lessen the time it takes to find pertinent reading material and actually access it, this study suggests a system that gathers and combines data from multiple sources and organisations in real-time. Reducing the time between finding and consuming content is the main goal. Bridging this gap is crucial since information access can be expensive, especially for those with limited internet availability. The goal of this research is to create a technique that drastically cuts down on the amount of 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 amounts of data from academics, researchers, educators, and policymakers throughout time. The algorithms that can partially automate certain tasks are then trained using this big data. Therefore, information access can be significantly improved by the insights gained from analysing this large, integrated library data. 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 marginalised and underprivileged populations.