"Role of Component Based Systems in Data Mining & Cloud Computing"

In this paper we proposed a "Collaborative approach" which tells how component based systems are used with data mining as well as cloud computing. Data Mining helps for extracting potentially useful information from the raw data. The function of association rules are an important data mining technique used to find the interesting relationship with the other related objects. The logical significance to study the concept of dependency in component based systems with data mining is to show the relation between one or more products where a change of one season to another season leads to a potential for a change of one product offer to another product offer. These association rules can either be use at a single level or in multiple levels. Sometimes, association rules becomes important because of output of one rule may be act as an input for other rules. In this way, we can say that limited numbers of association rules are generated at different levels. Data mining techniques help businesses to become more efficient by reducing costs. Here, we uses two types of data mining techniques called "Feature Selection & feature extraction" and "Attribute importance" which helps us for "Product Mining". Data mining techniques and applications are very much needed in the cloud computing paradigm. When we implement data mining techniques with cloud computing then it will allow the users to retrieve meaningful information from virtually integrated data warehouse that reduces the costs of infrastructure. The major benefit to combine component based systems with cloud computing is it is very easy to use with "platform as a service". The other benefits to combine these concepts are making systems more reliable, well maintained and also cost effective.