Developing Data Quality Aware Applications
Ricardo Pérez‐Castillo, César Guerra-García, Mario Piattini, Ma Ángeles Moraga
Abstract
Ricardo Pérez‐Castillo, César Guerra-García, Mario Piattini, Ma Ángeles Moraga
Abstract
Inadequate levels of Data Quality (DQ) in Information Systems (IS) suppose a very important problem for organizations. In any case, they look for to assure data quality from earlier stages on information system developments. This paper proposes to incorporate mechanisms into software development methodologies, in order to integrate users DQ requirements aimed at assuring the data quality from the beginning of development. It brings a framework consisting of processes, activities and tasks, well defined, which would be incorporated in existent software development methodology, as METRICA V3; and therefore, to assure software product data quality created according to this methodology. The extension presented, is a guideline, and this can be extended and applied to other development methodologies like Unified Development Process.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Inadequate levels of Data Quality (DQ) in Information Systems (IS) suppose a very important problem for organizations. In any case, they look for to assure data quality from earlier stages on information system developments. This paper proposes to incorporate mechanisms into software development methodologies, in order to integrate users DQ requirements aimed at assuring the data quality from the beginning of development. It brings a framework consisting of processes, activities and tasks, well defined, which would be incorporated in existent software development methodology, as METRICA V3; and therefore, to assure software product data quality created according to this methodology. The extension presented, is a guideline, and this can be extended and applied to other development methodologies like Unified Development Process.
Key concepts: Computer science, Quality (philosophy), Software quality, Software development process, Software development, Process (computing), Software engineering, Data quality