Big Data Analytics Technologies and Implementation Challenges for Smart Infrastructure Development in Malaysia: A Narrative Review
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Abstract
This paper reviews Big Data Analytics (BDA) applications for traffic management and security monitoring in Malaysian urban infrastructure, examining implementation barriers and scaling requirements for effective adoption. Through an analysis of international case studies from Singapore, São Paulo, and comparable cities, the review identifies four primary barriers preventing the scaling of integrated BDA in Malaysian cities: technological infrastructure gaps, governance fragmentation, regulatory inadequacies, and implementation capacity constraints. Despite recent legislative developments, including the Data Sharing Act 2025 and existing BDA implementations such as Malaysia City Brain, implementation barriers persist due to Malaysia's federal governance structure and infrastructure limitations, which differ significantly from those of successful city-state implementations. This study proposes a contextualised five-priority implementation approach that emphasises expanding existing corridor-based pilots, leveraging federal coordination mechanisms through the Data Sharing Act 2025, regulatory development, strategic partnerships, and performance measurement systems. The analysis reveals that governance coordination and the development of a regulatory framework should guide the scaling of infrastructure investments for effective BDA adoption. These findings provide Malaysian policymakers with a realistic scaling pathway that builds upon existing implementations, working within institutional and resource constraints to develop integrated urban analytics systems for traffic optimisation and security monitoring.
Manuscript received: 9 Jun 2025 | Revised: 17 July 2025 | Accepted: 24 Sep 2025 | Published: 31 Mar 2026
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