MAMD 2.0: Environment for data quality processes implantation based on ISO 8000-6X and ISO/IEC 33000

摘要

Organizations are increasingly becoming realized that the higher the levels of quality of data they use in their business processes, the larger the organizational performance can be. Therefore, it is highly recommended to pay special attention to data quality by institutionalizing a set of the best practices related to the disciplines of data-related disciplines, namely, data management, data quality management and data governance. After investigated on the field, and because of our research, we developed MAMD - Modelo Alarcos de Mejora de Datos-, a framework for assessing and improving the levels of data quality in organizations, in which we aligned and established the relationships between the three disciplines. Our aim was to provide organizations with sound artefacts, which can help them to efficiently implement data-related strategies to achieve adequate levels of data quality, and consequently, better organizational performance. Grounding our proposal on a process-oriented approach, we initially developed two components for MAMD: (1) a process reference model addressing the best practices of the previously mentioned data-related disciplines, and (2) an assessment and improvement model of the level of implantation of these practices. The process reference model is based on the principles of ISO 8000-61, which we complemented by adding specifics on data governance processes, and specifics on data management processes. The evaluation model is grounded on ISO 8000-62, and therefore aligned to ISO/IEC 33000. After having tested the usability of MAMD in several case studies, and after having analysed the conclusions raised from the learnt lessons, this paper describes the changes we introduced to the first version of MAMD to make the framework easier to apply (more easily auditable, and more easily implementable by consultancy). The paper also describes the application of the new version of MAMD to a new case study to check the efficiency of the changes. So, the main contribution of this paper is the presentation of the new version of MAMD.