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An Empirical Analysis of Different Big Data-based AI Integrated Tools in Multidisciplinary Fields

Le Trung Min Sharmila Mathivanan
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An Empirical Analysis of Different Big Data-based AI Integrated Tools in Multidisciplinary Fields

by Le Trung Min, Sharmila Mathivanan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 62
Year of Publication: 2025
Authors: Le Trung Min, Sharmila Mathivanan
10.5120/ijca2025924430

Le Trung Min, Sharmila Mathivanan . An Empirical Analysis of Different Big Data-based AI Integrated Tools in Multidisciplinary Fields. International Journal of Computer Applications. 186, 62 ( Jan 2025), 20-33. DOI=10.5120/ijca2025924430

@article{ 10.5120/ijca2025924430,
author = { Le Trung Min, Sharmila Mathivanan },
title = { An Empirical Analysis of Different Big Data-based AI Integrated Tools in Multidisciplinary Fields },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2025 },
volume = { 186 },
number = { 62 },
month = { Jan },
year = { 2025 },
issn = { 0975-8887 },
pages = { 20-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number62/an-empirical-analysis-of-different-big-data-based-ai-integrated-tools-in-multidisciplinary-fields/ },
doi = { 10.5120/ijca2025924430 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-01-28T19:07:12+05:30
%A Le Trung Min
%A Sharmila Mathivanan
%T An Empirical Analysis of Different Big Data-based AI Integrated Tools in Multidisciplinary Fields
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 62
%P 20-33
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The exponential data growth in today's world necessitates efficient and intelligent data management solutions. Machine learning has emerged as a key technology for addressing the challenges posed by big data, offering the potential to automate tasks, optimize processes, and extract valuable insights from massive datasets. This research explores the role of machine learning in data management across various fields, examining its applications, benefits, and potential drawbacks. The study also delves into the ethical considerations surrounding AI adoption, such as bias, fairness, and transparency. A comparative analysis of five prominent AI-powered data management tools is conducted, evaluating their performance, scalability, and resource utilization. The findings provide insights into the strengths and weaknesses of each tool, aiding in informed decision-making for organizations seeking to leverage AI for efficient and responsible data management in the era of big data.

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Index Terms

Computer Science
Information Sciences

Keywords

Data Management Big Data Artificial Intelligence (AI) Data Integration Multidisciplinary Field Cloud Computing Ethical Considerations.

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