Análisis de rendimiento académico estudiantil usando data warehouse y redes neuronales/Analysis of students' academic performance using data warehouse and neural networks

Every day organizations have more information because their systems produce a large amount of daily operations which are stored in transactional databases. In order to analyze this historical information, an interesting alternative is to implement a Data Warehouse. In the other hand, Data Warehouses...

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Bibliographic Details
Published in:Ingeniare : Revista Chilena de Ingenieria 2011-12, Vol.19 (3), p.369-381
Main Authors: Matamala, Carolina Zambrano, Díaz, Darío Rojas, Cuello, Karina Carvajal, Leiva, Gonzalo Acuña
Format: Article
Language:eng ; spa
Subjects:
análisis histórico
Data warehouse
Data warehouses
Historical analysis
información estratégica
Neural networks
predicción
prediction
Predictions
redes neuronales
strategic information
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Summary:Every day organizations have more information because their systems produce a large amount of daily operations which are stored in transactional databases. In order to analyze this historical information, an interesting alternative is to implement a Data Warehouse. In the other hand, Data Warehouses are not able to perform predictive analysis for themselves, but machine learning techniques can be used to classify, grouping and predict historical information in order to improve the quality of analysis. This paper depicts architecture of a Data Warehouse useful to perform an analysis of students' academic performance. The Data Warehouse is used as input of a Neural Network in order to analyze historical information and forecast. The results show the viability of using Data Warehouse for academic performance analysis and the feasibility of predicting the number of approved courses for students using only their own historical information. [PUBLICATION ABSTRACT]
ISSN:0718-3291
0718-3305