Resumen
This article focuses on online analytical processing, data mining and data warehouses which have emerged during the last decade to address the problem of executives, managers and analysts. An open framework for the development of data mining algorithms and decision support systems should include capabilities to analyze huge datasets, cluster data, build classification models, and extract associations and patterns from input data. The data miner or the user of the system has to analyze large datasets and he or she needs to make use of data mining tools to perform a task. Data is gathered and data mining algorithms are used in order to build knowledge models that summarize the input data. Those models may provide the information our user needs, or they may just suggest new ways to explore the available data. Moreover, those knowledge models could be used as input to other mining algorithms in order to solve second-order data mining problems. Both knowledge model and dataset metadata might be stored for later use in the back-end database.