Publicação
Assessing the Level of Data Governance Implementation in a Portuguese Insurance Company using DAMA DMBOK Framework
| Resumo: | A structured governance is essential to guarantee data quality, accountability, and compliance with legal and business requirements as enterprises increasingly acknowledge data as a strategic asset. This thesis measures the level of Data Governance implementation within an insurance company, using the Data Management Association (DAMA) Data Management Body of Knowledge (DMBOK) framework as structural guidance and a customized maturity assessment model. The maturity model was developed by selecting eight core Knowledge Areas (KA) from DAMA-DMBOK’s eleven, considered the most relevant to the organization’s context, and was applied a five-level maturity scale inspired by the Capability Maturity Model Integration (CMMI) approach. A structured methodology supported by a questionnaire was used to gather insights and perspectives from key stakeholders across business and Information Technology (IT) departments. Each area was assessed, allowing to measure the maturity score of its practices. This thesis also establishes target levels that were aligned with internal priorities and stakeholder knowledge, allowing do develop actionable recommendations to enhance governance practices. These recommendations were developed in accordance with DAMA-DMBOK principles and adapted to the organization’s context and resources. The assessment revealed that the biggest gaps between current practices and desired maturity levels lies in Data Governance and Data Architecture areas. To guide implementation, a roadmap developed based on the recommendations is suggested, outlining key actions and responsibilities across people, processes, and technology. Thisthesis aims to support the shift to a more developed, long-lasting, and business-aligned data governance model by providing an organized diagnosis and a useful improvement path. |
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| Autores principais: | Baptista, Henrique de Oliveira |
| Assunto: | DAMA-DMBOK Maturity Assessment Data Governance Data Management SDG 9 - Industry, innovation and infrastructure SDG 16 - Peace, justice and strong institutions SDG 17 - Partnerships for the goals |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso embargado |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | A structured governance is essential to guarantee data quality, accountability, and compliance with legal and business requirements as enterprises increasingly acknowledge data as a strategic asset. This thesis measures the level of Data Governance implementation within an insurance company, using the Data Management Association (DAMA) Data Management Body of Knowledge (DMBOK) framework as structural guidance and a customized maturity assessment model. The maturity model was developed by selecting eight core Knowledge Areas (KA) from DAMA-DMBOK’s eleven, considered the most relevant to the organization’s context, and was applied a five-level maturity scale inspired by the Capability Maturity Model Integration (CMMI) approach. A structured methodology supported by a questionnaire was used to gather insights and perspectives from key stakeholders across business and Information Technology (IT) departments. Each area was assessed, allowing to measure the maturity score of its practices. This thesis also establishes target levels that were aligned with internal priorities and stakeholder knowledge, allowing do develop actionable recommendations to enhance governance practices. These recommendations were developed in accordance with DAMA-DMBOK principles and adapted to the organization’s context and resources. The assessment revealed that the biggest gaps between current practices and desired maturity levels lies in Data Governance and Data Architecture areas. To guide implementation, a roadmap developed based on the recommendations is suggested, outlining key actions and responsibilities across people, processes, and technology. Thisthesis aims to support the shift to a more developed, long-lasting, and business-aligned data governance model by providing an organized diagnosis and a useful improvement path. |
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