Data mining: Application of digital marketing in education

Abstract

The excessive cost of inadequate management of stored information resources by companies means a significant loss for them, causing them to invest more than they should in technology. To overcome and avoid more significant losses, companies must counteract this type of problem. The present work's aim is to apply good data mining through digital business marketing that will allow ordering and filtering of the relevant information in the databases through RapidMiner, to supply the companies' databases with only relevant information for the normal development of their functions. For this purpose, the Knowledge Discovery Databases (KDD) methodology will be used, which will allow us to filter and search for information patterns that are hidden in order to take advantage of the historical data of investment per student in the educational sector and to establish a more accurate and efficient data prediction. As a result, it was found that over the years, the expenditure per student increases regardless of the area in which it is located, that although not in all provinces same amount is allocated, it is observed that it maintains an upward trend concerning the expenditures made, concluding that the KDD methodology allowed us to graph and showed how the expenditure allocated to the education sector has varied in the different grades of education, providing relevant information that will be useful for future related studies.