The Thesis aims at understanding a Data Warehouse, its types, the underlying architecture and designs, and then primarily focuses on what is Data Mining, how does it help, where it is used, the new Trends and Techniques and then analysis to recommend the techniques that can be used to integrate with different Data Warehouses. Research work focuses on the different Data Mining tools available in the market, how they compare with each other with respect to the platforms they support, algorithms used in the software, their input and output capabilities, limitations, integration to different tools applications, cost, front end options to Business, strengths and weaknesses, and ease of use. Then, a sample data set is used to identify the different Data Mining Tools and Techniques that can be used and then compare their output results and finally arrive to a conclusion.
