A Scalable Artificial Intelligence Framework for Intelligent Data Analysis

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Authors: Shajini R
Cited by: 0

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