A governança dos dados como facilitadora para transformação digital no contexto do DETRAN/DF

• Ano de defesa: 2023
• Autor(a) principal: Soares, Raul Coelho
• Orientador(a): Anjos, Priscila Caneparo dos
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Católica de Brasília
• Programa de Pós-Graduação: Programa Stricto Sensu em Governança, Tecnologia e Inovação
• Departamento: Escola de Educação, Tecnologia e Comunicação
• País: Brasil
• Palavras-chave em Português: Governança de dados; Interoperabilidade; Transformação digital; Inovação
• Palavras-chave em Inglês: Data governance; Interoperability; Digital transformation; Innovation
• Área do conhecimento CNPq: CNPQ::CIENCIAS SOCIAIS APLICADAS
• Link de acesso: https://bdtd.ucb.br:8443/jspui/handle/tede/3313

Digital transformation (DT) has been a recurring theme in several areas, motivated by the increasing adoption of technologies. In the transit area, the services offered by the Traffic Departments (DETRANs) of the 26 (twenty-six) Brazilian states and the Federal District (DF) had significant changes in legislation. Since 2021, the new rules have allowed digital documents to replace physical ones. To carry out these TDs at the DETRANs, it was necessary to work together with various bodies from the Traffic area (Road and Highway Departments - DERs, State Transit Companies -CIRETRANs, Federal Highway Police - PRF and National Department of Infrastructure and Transport). Aiming for integration among all bodies, the National Traffic Secretariat (Senatran) has been managing an integrated National Base of Vehicles and Drivers, which requires effective Data Governance (GD). This dissertation depicts a methodology of qualitative research that explores descriptive studies in TD and GD at a sufficient level to support the case study of the Department of Transit of the Federal District (DETRAN/DF) in the last two years. A study of the Institutional Strategic Planning (PEI) (2021-2023) of DETRAN/DF was carried out to support the identification of attributions, responsibilities and objectives. A questionnaire has been applied to specialists from the areas aiming to evaluate and complete the suggested model, which was elaborated based on the legislation in the PEI. However, there is still further investigation on how DG can contribute to creating value in the organization such as improving data quality and security, standardizing processes involving data, and optimizing decision-making. In addition, promoting a vision macro of the data would enable advances in DETRAN/DF services. Thus, this study presents a contribution to the DG and TD research area, mainly regarding better explanations for the identification of master data and improvement of process efficiency in public sector organizations, such as DETRAN/DF.