In modern manufacturing environments, vast amounts of data are collected in database management systems and data warehouses from all involved areas. Data mining is the nontrivial extraction of implicit, previously unknown, and potentially useful information from data. It is the extraction of information from huge volume of data or set through the use of various data mining techniques. The data mining techniques like clustering, classification help in finding the hidden and previously unknown information from the database. In addition, data mining also important role and educational sector. Educational Data Mining (EDM) is a field of analysis and research where various data mining tools and techniques are used to optimize the applications in education sector. The paper aims to analyze the enormous data from the education sector and provide solutions and reports for specific aspects of education sector such as student’s performance and placements. Moreover, this paper reviews the literature dealing with knowledge discovery and data mining applications in the broad domain of manufacturing with a special emphasis on the type of functions to be performed on the data. The major data mining functions to be performed include characterization and description, association, classification, prediction, clustering and evolution analysis.
Data Mining, EDM, Manufacturing, Literature review
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