Development of scalable tool for big data analysis and visualization

Abstract

The rapid growth of big data has created an urgent need for tools that can efficiently process, analyze, and visualize large datasets while remaining accessible to non-technical users. Existing solutions are either insufficiently scalable to accommodate the volume, variety, and velocity of modern data, or they are challenging for average users. This thesis addresses these issues by creating a scalable and user-friendly toolbox for large data analysis and visualization. The proposed solution makes use of modern technologies such as Apache Spark for distributed data processing, Python with FastAPI for backend services, and React with D3.js for creating dynamic, interactive web-based visualizations.