Abstract: The growing strategic importance of data has increased organizational interest in Data Governance (DG) as a mechanism to ensure data quality, security, compliance, and value generation. Despite the widespread adoption of DG initiatives, organizations continue to face substantial implementation difficulties that limit the effective use of data for decision-making and innovation. This study presents a Systematic Literature Review conducted in accordance with the PRISMA framework to identify and synthesize the main challenges associated with DG implementation. A total of 38 empirical studies published between 2017 and 2025 were analyzed. The findings reveal five recurrent dimensions of implementation challenges: organizational, cultural, technical, quality, and regulatory. Frequently reported issues include insufficient resources, shortage of specialized personnel, resistance to organizational change, data silos, interoperability limitations, poor data quality, and increasing regulatory complexity. The review also shows that formal governance frameworks provide implementation guidance but do not fully eliminate these barriers. Based on the synthesized evidence, the study also proposes an interpretive conceptual model to illustrate how these barriers may emerge and reinforce one another during DG implementation. The study concludes that successful DG implementation depends on aligning organizational capabilities, technological infrastructure, and regulatory practices within an integrated governance strategy that supports data-driven value creation.

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