DATA MINING METHODOLOGIES

Abstract

Data mining methodologies encompass a range of techniques and processes aimed at
extracting meaningful patterns, trends, and insights from large datasets. These methodologies
typically involve various stages such as data preprocessing, model selection, pattern discovery,
and evaluation. Common data mining techniques include classification, clustering, association rule
mining, and anomaly detection. The choice of methodology depends on the specific goals of the
analysis and the nature of the data being examined. This paper provides an overview of different
data mining methodologies, their applications, advantages, and challenges.