Published Paper Details:

Data complexity is a major consideration when scaling the data. Integration of heterogeneous data sets helps solve big data difficulties. Large-scale databases are difficult to comprehend and analyze since they require a lot of processing and storage space. With the rapid growth of data, extracting it in a fashion that the human mind can understand is becoming increasingly difficult. An introduction of Big Data research issues and triumphs, as well as the methodology and tools used to visualize it, will be discussed in this session. As a result, the primary purpose of this work is to summarize and provide novel solutions for the present state-of-the-art in Big Data visualization. Data types, analytical methodologies, and visualization techniques and tools are categorized in this study, with a special focus on the evolution of visualization methods over the last few years. The findings of the study show that there is still a disparity between the two groups. With regard to data visualization, the tools and applications we tested didn't have much support for advanced techniques like radial or temporal data display. Professional data analysts are eager to learn and use new tools and approaches, according to interviews. Exploratory analytic approaches are of particular relevance to users, as they can assist in their workflow.