Application of Data Mining Techniques to a Selected Business Organisation with Special Reference to Buying Behaviour

TL;DR

This paper explores how data mining techniques like association rule mining, rule induction, and Apriori algorithm can analyze large shopping mall databases to uncover buying behaviors, aiding organizational decision-making.

Contribution

It demonstrates the application of specific data mining techniques to real-world retail data to extract meaningful buying patterns.

Findings

Identification of buying behavior patterns

Effective use of Apriori algorithm for market basket analysis

Insights into customer purchasing habits

Abstract

Data mining is a new concept & an exploration and analysis of large data sets, in order to discover meaningful patterns and rules. Many organizations are now using the data mining techniques to find out meaningful patterns from the database. The present paper studies how data mining techniques can be apply to the large database. These data mining techniques give certain behavioral pattern from the database. The results which come after analysis of the database are useful for organization. This paper examines the result after applying association rule mining technique, rule induction technique and Apriori algorithm. These techniques are applied to the database of shopping mall. Market basket analysis is performing by the above mentioned techniques and some important results are found such as buying behavior.