BIG DATA ANALYTICS FRAMEWORK FOR VISION 2030 PERFORMANCE MONITORING AND NATIONAL KPIS

Authors

DOI:

https://doi.org/10.18623/rvd.v23.5732

Keywords:

Big Data Analytics, Vision 2030, National KPIs, Performance Monitoring, Digital Governance, Predictive Analytics, Data Integration, Public Sector Intelligence, Strategic Performance Management

Abstract

Saudi Arabia’s Vision 2030 is a comprehensive transformation strategy that includes measurable strategic objectives and performance measures. To effectively monitor the national Key Performance Indicators (KPIs), it is necessary to use advanced data integration, predictive analytics, and performance intelligence technology. Conventional performance reporting is not effective in managing a large-scale transformation strategy. This study aims to introduce a comprehensive Big Data Analytics Framework that can effectively support the performance monitoring of Vision 2030 and national KPIs. The study aims to introduce a comprehensive Big Data Analytics Framework that includes data ingestion, real-time analytics, predictive analytics, performance scoring, and performance intelligence under a unified framework of governance. This study also aims to introduce a National Performance Intelligence Index (NPII) model to measure aggregated performance of national transformation strategies. The study results show that a centralized big data performance ecosystem can effectively enhance KPI accuracy, reporting speed, and transparency to achieve effective policy intervention strategies. This study also aims to show that a conventional performance monitoring system can effectively integrate predictive analytics to enhance accountability, speed, and measurable performance to achieve strategic objectives of Vision 2030.

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Published

2026-04-15

How to Cite

Gulam, G. (2026). BIG DATA ANALYTICS FRAMEWORK FOR VISION 2030 PERFORMANCE MONITORING AND NATIONAL KPIS. Veredas Do Direito, 23(6), e235732. https://doi.org/10.18623/rvd.v23.5732

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Vol. 23 No. 6 (2026): Veredas do Direito, v. 23, n. 6 2026

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