Analyzing and Improving Data Quality


  • Agustina Buccella GIISCO Research Group, Departamento de Ciencias de la Computación, Universidad Nacional del Comahue, Neuquen, Argentina
  • Alejandra Cechich GIISCO Research Group, Departamento de Ciencias de la Computación, Universidad Nacional del Comahue, Neuquen, Argentina
  • Gonzalo Domingo Proyectos de Telesupervisión y Geociencias, D.S.I. Cuenta E&P - Argentina Sur, Repsol YPF


data life cycle


Data quality is a research area strongly investigated during the 90’s. However, few companies in Argentina apply data quality methodologies or tools during the analysis, design or implementation phases of software development process. Developers generally use techniques to design systems such as UML without considering mechanisms for future data quality problems. In this work we propose a methodology in which the data quality is an essential part of the whole software development process. Early design decisions on data quality strongly impact on the system. Our methodology defines a set of practices to be applied on the software life cycle. In addition these practices act as a means to evaluate if systems already running fulfill with minimal data quality requirements.


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How to Cite

Buccella, A., Cechich, A., & Domingo, G. (2008). Analyzing and Improving Data Quality. Journal of Computer Science and Technology, 8(02), p. 57–63. Retrieved from



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