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Analysis and processing of academic data from a higher institution with tools for big data

Abstract:

This work presents an analysis of some terms related to Big Data, Hadoop, and their architecture; in addition, it presents the results of the analysis of undergraduate enrollment information of the distance system of Universidad Tecnica Particular de Loja (UTPL), this information is extracted from academic system by using Hadoop framework as a big data processing platform; for that, a big data infrastructure has been designing and tested which is based on Hortonworks and Power View tools in order to present reports that helps managers to have metrics in order to improve their decision making. For this, a thorough search of information by using Hadoop framework, in which a synthesis of the different important terms was made, it reaches to determine different areas of application; in addition it presents a big data case study by of undergraduate enrollment information from academic system of UTPL by using the Hadoop framework. Consequently, it is concluded that Hadoop Framework helps us to process of big data sets, because it has Hadoop Distributed File System which provides an increased performance for data, and MapReduce process the data in parallel with the integration of Hortonworks and Power View tools which allow to analyze big data and to present reports in maps in order to analyze UTPL students enrollment.