A Comparative Study of Data Visualization Tools for Large-Scale Data Analytics in the Emerging 6G and IoT Era


EOI: 10.11242/viva-tech.01.09.24

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Citation

Prof. Nitesh Kumar, Chandan Kumar, Vivekanand Pasi,"A Comparative Study of Data Visualization Tools for Large-Scale Data Analytics in the Emerging 6G and IoT Era" VIVA-IJRI Volume 1, Issue 9, Article 6, pp. 1-6, 2026. Published by MCA Department, VIVA Institute of Technology, Virar, India.

Abstract

The rapid growth of Internet of Things (IoT) technologies and the development of sixth-generation (6G) communication networks have resulted in the generation of very large volumes of data at extremely high speed. Smart sensors, connected devices, and intelligent systems continuously generate data related to monitoring, communication, and decision-making. Managing and analyzing such large-scale data in real time has become a major challenge for modern data analytics systems. Traditional data analysis approaches are often not sufficient to handle the complexity, velocity, and scale of data generated in 6G-enabled IoT environments. Data visualization plays an important role in converting complex and unstructured data into meaningful visual formats that are easy to understand. Visualization techniques help analysts and decision-makers to identify trends, patterns, and anomalies in large datasets. This paper presents a comparative study of commonly used data visualization tools such as Tableau, Microsoft Power BI, D3.js, and Apache Superset. The comparison is based on scalability, performance, flexibility, and ease of use. The study shows that enterprise visualization tools are user-friendly and suitable for moderate data volumes, while open-source tools provide better scalability for large-scale data analytics. This research work helps MCA students and researchers understand the importance of selecting appropriate visualization tools for future 6G-IoT applications.

Keywords

Data Visualization, IoT Analytics, Large-Scale Data, Power BI, 6G Networks

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