The paper describes a Web-based application's scientific protocols, features, and predictive process for tracking global competitiveness and sustainability dynamics in an emerging economy, the Sultanate of Oman. This comprehensive exploration spans diverse dataset domains, notably (i) the global competitiveness index, (ii) United Nations SDGs, (iii) environmental, social, and governance (ESG) datasets, (iv) vital macroeconomic data and (v) Oman Vision 2040. The work is part of a larger project that examines the application of big data technologies to support robust, sustainable economic management. System. The present contribution documents the results of a web-based predictive enterprise business intelligence system experiment conducted over the past two years. The work focused on developing Oman's global competitiveness and sustainability monitoring system for real-time tracking of efforts towards achieving the country's economic management strategy in line with Oman Vision 2040. Few academic research has experimented with applying multi-criteria analysis to World Economic Forum data, among other voluminous and diverse datasets, on global competitiveness and sustainability in transitioning economies like Oman. The present contribution involves evolving multiple sets of country-specific data, methodological considerations, and the need for comparability in results in the rapidly changing information systems landscape. Fundamentals of creating websites using technologies like HTML, CSS, and JavaScript were deployed to design and build a website with a backend MySQL database, ensuring the website's user interface. Exploratory qualitative data mining tools such as Microsoft PowerBI and Orange data mining tools were deployed for ribbon visualisation of prior literature, thematic clustering, and classification.

JEL Codes:

Keywords: Big data technologies; ESG, GCSMS, Global competitiveness; Oman Vision 2040, SDGs; Sustainability.