Abstract: In the era of digital transformation, businesses are increasingly relying on data-driven approaches to enhance the quality and effectiveness of decision-making. The rapid growth of data generated from various sources such as transactions, social media, and organizational systems has created a need for advanced analytical tools. In this context, data mining techniques have emerged as powerful tools for extracting meaningful patterns, relationships, and trends from large datasets. This study examines the impact of data mining techniques on business decision-making, highlighting how these techniques support strategic, tactical, and operational decisions across different business functions.
The study explores key data mining techniques such as classification, clustering, association rule mining, regression, and anomaly detection, and their applications in areas including marketing, finance, human resource management, and supply chain operations. These techniques enable organizations to gain deeper insights into customer behavior, predict future trends, identify risks, and improve operational efficiency. The integration of data mining with technologies such as machine learning, artificial intelligence, and big data analytics further enhances the accuracy and speed of decision-making processes.
The findings suggest that data mining significantly improves decision quality by reducing uncertainty, enabling predictive analysis, and supporting evidence-based management practices. It also helps organizations achieve competitive advantage by facilitating personalized customer engagement and efficient resource utilization. Overall, data mining techniques play a crucial role in transforming traditional decision-making processes into intelligent, data-driven systems that enhance organizational performance and sustainability in a highly competitive business environment.
Keywords: Data Mining, Business Decision, Artificial Intelligence, Business Environment.
Title: Impact of Data Mining Techniques on Business Decision-Making – An Conceptual Framework
Author: Dr.Umamaheswari.S, Abdul Rouf J, Vijaykumar V
International Journal of Management and Commerce Innovations
ISSN 2348-7585 (Online)
Vol. 14, Issue 1, April 2026 - September 2026
Page No: 199-202
Research Publish Journals
Website: www.researchpublish.com
Published Date: 21-April-2026
