Organizations increasingly depend on reliable, ethical, and evidence-based data practices, yet the literature reveals persistent fragmentation in how Data Governance maturity is defined, operationalized, and measured. Existing frameworks provide robust functional structures and capability definitions but offer limited integration between assessment, decision logic, and prescriptive intervention. This article proposes the Data Operating Model & Maturity (DOMMx), an integrated, cross-domain and cross-layer system that unifies diagnostic evaluation, maturity triggers, and procedural guidance into a coherent operational model. The suffix “x” denotes the model’s extensibility and interactivity, reflecting its ability to operate across governance domains and implementation layers. DOMMx translates multidimensional governance constructs into measurable criteria, enables consistent scoring across all DAMA domains, and links maturity levels to standardized action codes supported by explicit prerequisites and deliverables. Its procedures consolidate principles from DAMA-DMBOK2, DCAM, CMMI, and the IDGC, providing a reproducible pathway for sustained capability evolution. The model supports both centralized and federated architectures and incorporates emerging requirements, such as privacy-by-design and responsible AI oversight. By bridging the gap between conceptual governance frameworks and the operational mechanisms required to advance organizational maturity, DOMMx provides a replicable, actionable, and evidence-based contribution to both research and practice.
Leonardo Guerreiro (Mon,) studied this question.