<![CDATA[Digital transformation has encouraged organizations from various sectors to optimize the use of data as a strategic asset in supporting decision-making, service innovation, and increasing operational efficiency. However, the complexity of information systems, the increasing volume of data, and the diversity of data sources and formats pose serious challenges in terms of data governance. In this context, data architecture becomes a crucial element that functions as a structured framework to systematically manage, integrate, and secure data. This study aims to explore the role of data architecture in improving the effectiveness of data governance amidst the demands of digital transformation. Through a qualitative approach with literature studies and analysis of best practices from various organizations, this article identifies core components of data architecture such as data modeling, metadata management, integration between systems, and information security mechanisms. The findings show that the implementation of a comprehensive data architecture can improve data quality, strengthen accountability, accelerate interoperability between systems, and create a strong foundation for the implementation of adaptive and sustainable data governance.In addition, data architecture also facilitates the creation of consistent standards and policies, thus helping organizations comply with regulations and increasing stakeholder trust. Thus, data architecture not only plays a role as a technical aspect, but also as a strategic enabler in supporting the success of digital transformation based on reliable, structured, and high-value data.]]>
