Intelligent and Distributed Data Warehouse for Student’s Academic Performance Analysis
In the academic world, a large amount of data is handled each day, ranging from student’s assessments to their socio-economic data. In order to analyze this historical information, an interesting alternative is to implement a Data Warehouse. However, Data Warehouses are not able to perform predictiv...
- Autores:
-
Silva, Jesús
Hernández, Lissette
Varela, Noel
Pineda Lezama, Omar Bonerge
Tafur Cabrera, Jorge
Lucena León Castro, Bellanith Ruth
Redondo Bilbao, Osman
Pérez Coronel, Leidy
- Tipo de recurso:
- http://purl.org/coar/resource_type/c_816b
- Fecha de publicación:
- 2019
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/5132
- Acceso en línea:
- http://hdl.handle.net/11323/5132
https://repositorio.cuc.edu.co/
- Palabra clave:
- Intelligent data retrieval
Data Warehouse
Unique Identification Number
Academic performance
- Rights
- openAccess
- License
- CC0 1.0 Universal
| Summary: | In the academic world, a large amount of data is handled each day, ranging from student’s assessments to their socio-economic data. In order to analyze this historical information, an interesting alternative is to implement a Data Warehouse. However, Data Warehouses are not able to perform predictive analysis by themselves, so machine intelligence techniques can be used for sorting, grouping, and predicting based on historical information to improve the analysis quality. This work describes a Data Warehouse architecture to carry out an academic performance analysis of students. |
|---|