DOS in Commerce, University of Mysore, Manasagangotri, Mysore-570 006
Online published on 31 October, 2011.
In today's market place consumers wanted every new gadget and machine and Companies began offering multiple products, hoping to compete by appealing to different consumer tastes.
Data mining is the analysis of (often large) observational data sets to find unsuspected relationships and to summarize the data in novel ways that are both understandable and useful to the data owner.
The relationships and summaries derived through a data mining exercise are often referred to as models or patterns. Examples include linear equations, rules, clusters, graphs, tree structures, and recurrent patterns in time series.
Market basket analysis requires the analysis and mining of large volumes of transaction data for making business decisions. It has become a key success factor in business. Effective market basket analysis techniques employ association rule and clustering as methods of analyzing such data. Business transactions often consist of several products (items) that are purchased together. Understanding the relationships across hundreds of product lines and among millions of transactions provides visibility and predictability of product affinity. An example of market basket analysis is that 85% of the people who buy a printer also buy paper at the same time.
