Big Data Network Formation and Data Centers in Uzbekistan's Digital Economy
Abstract
Big data infrastructure has a critical enabling role to play in supporting emerging economies towards their transition to data-driven systems and digitally resilient practices within the context of a national digital transformation agenda. The main objective of this study is to identify structural linkages and technological determinants that may favor network formation in Uzbekistan's data economy. Therefore, the present research aimed at analyzing large-scale data infrastructure initiatives through a comprehensive conceptual mapping of the digital ecosystem to estimate the extent of their operational contribution in different regional clusters. Regression analysis, which is a quantitative modeling tool for causal inference, was employed to simulate the relationship between data center expansion and network formation events. In addition, SUM-based modeling was applied to predict the trend of data traffic flows with two strategies: linear aggregation and weighted summation. The results show that both strategies can adequately simulate the relationship between infrastructure density and digital service usage, with all simulation accuracies above 92%. Based on the results, an action framework is proposed, including key components such as (1) interoperable data exchange protocols, (2) regional data hub prioritization, and (3) scalable bandwidth planning, setting mandatory data localization targets. Finally, some recommendations for implementing big data ecosystems in Uzbekistan were identified. Implications for policy makers include the value of engaging technology providers early, ensuring regulatory alignment, and testing system architectures continuously.