A Scalable Artificial Intelligence Framework for Intelligent Data Analysis
Abstract
The exponential growth of digital data in modern industries has created an urgent need for intelligent and scalable data analysis systems. Conventional data analytics techniques face serious challenges such as poor scalability, high processing time, and limited adaptability when handling large and complex datasets. Artificial Intelligence (AI) offers advanced capabilities such as learning, prediction, and pattern recognition, making it highly suitable for intelligent data analysis. This paper proposes a Scalable Artificial Intelligence Framework for Intelligent Data Analysis that integrates data preprocessing, machine learning models, analytical engines, and visualization modules into a unified architecture. The proposed framework automates data handling, improves analytical accuracy, and supports scalability across multiple domains. Experimental evaluation shows that the AI-based framework outperforms traditional approaches in terms of efficiency, flexibility, and performance.
Fields of Study & Subjects
Artificial Intelligence Applications
AI and Big Data Applications
Data Mining and Machine Learning Applications
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 12 February 2026
- Language
- EN