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Evolution of Data Mining: From Statistical Foundations to Big Data and Deep Learning

by Rajiv Chooramun
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 4
Year of Publication: 2025
Authors: Rajiv Chooramun
10.5120/ijca2025924837

Rajiv Chooramun . Evolution of Data Mining: From Statistical Foundations to Big Data and Deep Learning. International Journal of Computer Applications. 187, 4 ( May 2025), 12-20. DOI=10.5120/ijca2025924837

@article{ 10.5120/ijca2025924837,
author = { Rajiv Chooramun },
title = { Evolution of Data Mining: From Statistical Foundations to Big Data and Deep Learning },
journal = { International Journal of Computer Applications },
issue_date = { May 2025 },
volume = { 187 },
number = { 4 },
month = { May },
year = { 2025 },
issn = { 0975-8887 },
pages = { 12-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number4/evolution-of-data-mining-from-statistical-foundations-to-big-data-and-deep-learning/ },
doi = { 10.5120/ijca2025924837 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-05-17T02:45:52.928807+05:30
%A Rajiv Chooramun
%T Evolution of Data Mining: From Statistical Foundations to Big Data and Deep Learning
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 4
%P 12-20
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This article traces the historical development of data mining, outlining its evolution through four phases. It begins with the inception of statistical techniques in the 18th and 19th centuries, progresses through advancements in computer technology and artificial neural networks in the mid-20th century, and moves on to the establishment of foundational concepts and algorithms in the final decades of the 20th century. Finally, it addresses the incorporation of big data and deep learning technologies in the 21st century. A comprehensive literature review was conducted to explore the historical progression of data mining. The study examines contributions from early statistical analysis, the impact of electronic computers and database systems, the formalization of data mining concepts and algorithms during the 1990s, and recent advancements driven by big data and deep learning. Each phase has significantly advanced data mining methodologies. Early statistical analysis by figures such as Bayes and Gauss provided foundational groundwork. The advent of electronic computers and database systems enhanced data processing capabilities. The formalization of data mining in the 1990s, marked by ‘knowledge discovery in databases and algorithms like support vector machines, expanded its applications. In the 21st century, big data and deep learning have further elevated data mining, solidifying its importance in data science and diverse fields. While this review is limited by the scope of existing literature and historical context, it provides a comprehensive overview of data mining’s dynamic evolution and its critical role in extracting valuable insights from datasets. Future research could explore emerging developments and applications in this rapidly evolving field.

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Index Terms

Computer Science
Information Sciences
Data Mining
Machine Learning
Artificial Intelligence
Algorithms
Theory

Keywords

Data mining Artificial Intelligence Machine Learning Big Data Knowledge Discovery

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