Big data-based data visualization techniques for e-learning interactive data exploration

Social media, electronic correspondence, and company/institution websites provide rich data sources. This massive data and information dump is processed using the big data approach. The new definition has the potential to aid short of educational activities by facilitating a transition to an e-learning approach, increasing student engagement with their teachers, and boosting student outcomes. An advanced interactive data exploration for e-learning (AIDE-EL) framework is proposed in this research. This article examines how Big Data systems have evolved, their use in e-learning, and their impact on universities. A three-stage device design is built to assess, organize, and examine massive Cloud data sets in collaboration with universities. The suggested study uses the Gephi graphics platform to delve into unstructured material. The experimental results show the proposed method achieves an accuracy ratio of 95.2%, a likeness from the student and teacher of 94.3% and 96.1 %, and a user likeness ratio of 97.4%compared to other methods.