A literature study of bottlenecks in 2D and 3D Big Data visualization

Abstract: Context. Big data visualization is a vital part of today's technological advancement. It is about visualizing different variables on a graph, map, or other means often in real-time. Objectives. This study aims to determine what challenges there are for big data visualization, whether significant amounts of data impact the visualization, and finding existing solutions for the problems. Methods. Databases used in this systematic literature review include Inspec, IEEE Xplore, and BTH Summon. Papers are included in the review if certain criteria are upheld. Results. 6 solutions are found to reduce large data sets and reduce latency when viewing 2D and 3D graphs. Conclusions. In conclusion, many solutions exist in various forms to improve visualizing graphs of different dimensions. Future grows of data might change this though and might require new solutions of the growing data.