How Big Data Analytical Framework has Redefined Academic Sciences

Abstract

Academic institutions generate a large amount of heterogeneous data and academic leaders want to make the most of that data by evaluating it for improved decision-making. The volume is not the only difficulty; the organization's data format (structured, semi-structured, and unstructured) creates complication in academic functioning and decision-making on a daily basis. Academic data sets have expanded in amount and proportion to the point that standard data processing and analytics cannot provide satisfying results; moreover, it is not only about volume but also about what is to be done with data. In this paper, Big Data is used in an academic institution (University of Kashmir) to analyse data (structured, semi-structured, and unstructured) from multiple sources for smart decision-making, and machine learning models on Big Data are used to predict academic behaviour such as student performance, academic bias, and job market viability.