Circular Economy Practices for Data Management

Data waste presents a growing challenge in the digital era, characterized by redundant, outdated, and underutilized data that contributes to inefficiencies, increased costs, and environmental concerns. This paper explores how circular economy (CE) principles—reduce, reuse, recycle, repair, and rethink—can be adapted to optimize data usage, minimize waste, and ensure responsible data handling throughout its lifecycle. Applying CE concepts to data management can enhance sustainability, improve operational efficiency, and support responsible digital transformation. This study examines key strategies and challenges in implementing circular data management, emphasizing data reuse, lifecycle management, and policy frameworks. Furthermore, real-world examples and case studies demonstrate the impact of CE principles in reducing data waste and improving efficiency. Notably, AI-driven data minimization strategies have led to 30% reductions in storage costs, while centralized data-sharing initiatives have improved operational efficiency by 20%. These findings underscore the necessity of structured data governance in the digital economy.