Title
Data quality applied to an academic business intelligence solution: Lesson learned
Date Issued
26 October 2017
Access level
metadata only access
Resource Type
conference paper
Author(s)
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
(BACKGROUND) Business Intelligence covers a set of technologies allowing the extraction, transformation and loading of data into a data warehouse, and presents the information in a way that allows managers of an organization to make decisions. However, stored data in a warehouse does not always have the expected quality required and this can lead managers to make wrong decisions. (OBJECTIVES) The objective of this work is the development of a quality model applicable to an academic business intelligence solution, based on the ISO/IEC 25000 series of standards. (METHOD) In this research, an analysis of the data quality requirements was done, as an input for the respective evaluation. (RESULTS) The results obtained were presented in a radar chart, along with a textual analysis. (CONCLUSIONS) It could be concluded that data quality models and standards could be used successfully for evaluating the quality of an academic BI system. And this information is important for identifying and mitigating risks inherent to data and risks that depend on an information system.
Language
Spanish
OCDE Knowledge area
Sistemas de automatización, Sistemas de control
Subjects
Scopus EID
2-s2.0-85040233692
Source
2017 IEEE Colombian Conference on Communications and Computing, COLCOM 2017 - Proceedings
ISBN of the container
978-153861060-2
Conference
2017 IEEE Colombian Conference on Communications and Computing, COLCOM 2017
Sponsor(s)
La solución de BI comprende: (i) Un conjunto de procesos ETL que realizan la transformación de los datos fuente en información útil para el análisis; (ii) un Data Warehouse, utilizado para almacenar la información proveniente de los procesos ETL; que funciona como una base de datos relacional, pero usando conceptos típicos de BI como tablas de hechos y dimensiones; y (iii) una herramienta OLAP que toma los datos del Data Warehouse y permite la generación de reportes. De los 3 componentes mencionados, la última es la que realiza el mayor contacto con los usuarios, brindándoles acceso a la información utilizada para la toma de decisiones.
El desarrollo de este estudio, se puede decir que, se realizó en dos planos de trabajo: (i) el plano técnico que comprende la definición y evaluación del modelo de calidad de datos y (ii) el plano relacionado al proyecto ProCal-ProSer para la sistematización de la experiencia realizada.
Sources of information:
Directorio de Producción Científica
Scopus