Oliveira, Tiago H. Moreira deNeto, Miguel de CastroCosta, Eduardo GomesSimões, Matilde QueirósSousa, Cláudia2025-10-282025-10-16978-3-032-07988-6978-3-032-07989-32367-3370PURE: 132671446PURE UUID: 783ca725-ea1b-48c4-a72a-f2662087b4d3crossref: 10.1007/978-3-032-07989-3_3Scopus: 105020569987ORCID: /0000-0002-7265-3890/work/195065345http://hdl.handle.net/10362/189830Oliveira, T. H. M. D., Neto, M. D. C., Costa, E. G., Simões, M. Q., & Sousa, C. (2025). Rewiring Governance: Building a Data-Centric Ecosystem for Higher Education Strategic (and Digital) Transformation. In K. Arai (Ed.), Proceedings of the Future Technologies Conference (FTC) 2025 (Vol. 2, pp. 38-60). (Lecture Notes in Networks and Systems; Vol. 1676). Springer. https://doi.org/10.1007/978-3-032-07989-3_3Higher Education Institutions are facing increasing demands for transparency, agility, and stakeholder-centered services. Digital Transformation has emerged as a strategic response, requiring systemic change in culture, processes, and governance. At the core of this evolution is Learning Analytics, which, when combined with Business Intelligence and Business Process Management, offers a holistic foundation for data-informed decision-making. This study presents the case of NOVA Information Management School (NOVA IMS, Universidade NOVA de Lisboa), a leading public higher education institution in the field of data science, that designed and implemented an integrated analytics ecosystem entirely in-house. Grounded in Design Science Research, the study explores how dashboards, data governance, and process modelling converged to drive operational efficiency, strategic alignment, and institutional engagement. The initiative included over 100 BPMN-mapped processes, a real-time dashboard ecosystem (BI@NOVA IMS), and learning analytics tools embedded in academic, administrative, and sustainability workflows. Results include a reduction in reporting workload, faster decision-making, enhanced transparency, and alignment with the UN Sustainable Development Goals. Critical success factors include leadership commitment, internal capacity building, co-design practices, and ethical data governance. The findings contribute to the growing body of knowledge on DT in higher education and offer practical insights for institutional leaders seeking to implement similar models. The study concludes by identifying future opportunities for generative AI, personalised learning, and learning analytics integration into faculty development.231264381engDigital transformationLearning analyticsBusiness intelligenceHigher educationData governanceBPMMDashboard ecosystemControl and Systems EngineeringSignal ProcessingComputer Networks and CommunicationsSDG 4 - Quality EducationSDG 16 - Peace, Justice and Strong InstitutionsSDG 17 - Partnerships for the Goalsconference object10.1007/978-3-032-07989-3_3https://www.scopus.com/pages/publications/105020569987