Engenharia de dados no apoio à análise dos egressos de um curso de bacharelado em sistemas de informação

• Ano de defesa: 2023
• Autor(a) principal: Cardoso, Jackson
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Curitiba; Brasil; Programa de Pós-Graduação em Computação Aplicada; UTFPR
• Palavras-chave em Português: Inteligência coletiva; Computação em nuvem; Processo decisório; Banco de dados; OLAP technology; Sistemas de suporte de decisão; Estudantes universitários - Análise; Big data; Data integration (Computer service); Visual analytics; Intelligence service; Swarm intelligence; Cloud computing; Decision making; Data bases; Data Warehousing; Decision support systems; College students - Analysis; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO; Ciência da Computação
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/33000

Considering the ‘fragmentation/scattering of data’ and the need for support in analyzing the outcomes and employability of graduates, along with the motivation to outline data engineering, this work aims to explore the use of data engineering in supporting the decision-making process during the restructuring of the bachelor’s degree program in Information Systems at a Brazilian public university. Utilizing analytical data processing techniques, integrating information from various sources (university system, LinkedIn, and web forms), and providing key performance indicators (KPIs) for monitoring by decision-makers (coordinator and course board), a support tool was created for the strategic planning of the program. This tool features intuitive, cloudbased visual resources, enabling comprehensive data exploration and analysis. The goal is to foster the organization’s data intelligence, enabling collectively informed decision-making. The exploratory research addressed essential concepts and contributions on the subject, following a data engineering process applied to the analysis of graduates as a methodology for technology and knowledge generation. The resulting artifact was demonstrated to the user group in a corporate IT environment, obtaining feedback on its effectiveness in supporting decisionmaking.