ABSTRACT
Data mining is a process of discovering fascinating designs, new instructions and information from large amount of
sales facts in transactional and interpersonal catalogs. Since inventory databases, universal product bar codes and
scanners, and other such supply chain management technologies have been around for years, the idea of using data
to help manage retail operations is not new. However, more recently, the use of data mining to more thoroughly
understand patterns of consumer behavior that affect retail operations has become more prevalent. In order to
truly understand consumer behavior though, it is beneficial to understand both what they buy and who they are.
With this information, we can go beyond traditional inventory management, and craft a much more personalized
shopping experience for you. All organizations that collect, store, and analyze data have a responsibility to protect
privacy, to guard against misuse and abuse, and to share data only within the constraints of fairly developed and
disclosed policies. It will be able to expand and apply effective marketing strategies and in disease identification
frequent patterns are generated to discover the frequently occur diseases in a definite area. The conclusion in all
applications is some kind of association rules (AR) that are useful for efficient decision making.
Keywords: - Association rule mining, FP growth, decision making