Purpose: As data volumes expand exponentially, traditional data warehousing methodologies often struggle to meet the agility and scalability demands of modern enterprises. This study investigates the intersection of Cloud Computing, advanced data modeling techniques (specifically Data Vault), and Business Intelligence (BI) to understand how organizations can secure a sustainable competitive advantage.

Design/methodology/approach: The research employs a comprehensive architectural analysis and literature synthesis, examining the transition from legacy on-premise systems to cloud-native ecosystems. It evaluates the efficacy of Inmon, Kimball, and Data Vault methodologies when applied within modern Cloud ETL frameworks.

Findings: The analysis reveals that while traditional dimensional modeling remains relevant for the presentation layer, the Data Vault methodology offers superior adaptability for cloud-based data warehouses due to its decoupling of business keys and relationships. Furthermore, the adoption of cloud services is not merely an IT upgrade but a critical innovation driver that democratizes access to high-end BI and AI capabilities for SMEs.

Originality/value: This paper bridges the gap between technical data engineering concepts—such as hash-based integration and ELT pipelines—and strategic business outcomes, providing a roadmap for organizations seeking to leverage Big Data for innovation and market agility.

Cloud Computing, Data Vault, Business Intelligence, ETL

Golightly, L.; Chang, V.; Xu, Q.A.; Gao, X.; Liu, B.S.C. Adoption of cloud computing as innovation in the organization. Int. J. Eng. Bus. Manag. 2022, 14, 1–17. [CrossRef]

Vines, A.; Tanasescu, L. An overview of ETL cloud services: An empirical study based on user’s experience. In Proceedings of the International Conference on Business Excellence, Bucharest, Romania, 23–24 March 2023; Volume 17, pp. 2085–2098. [CrossRef]

Clissa, L.; Lassnig, M.; Rinaldi, L. How Big is Big Data? A comprehensive survey of data production, storage, and streaming in science and industry. Front. Big Data 2023, 6, 1271639. [CrossRef] [PubMed]

Inmon, W.H.; Zachman, J.A.; Geiger, J.G. Data Stores, Data Warehousing, and the Zachman Framework: Managing Enterprise Knowledge; McGraw-Hill: New York, NY, USA, 2008; ISBN 0070314292

Kimball, R.; Ross, M.; Thornthwaite, W.; Mundy, J.; Becker, B. Data Warehouse Lifecycle Toolkit: Practical Techniques for Building Data Warehouse and Business Intelligence Systems, 2nd ed.; Wiley: New York, NY, USA, 2008.

Linstedt, D. Data Vault Series 1—Data Vault Overview. The Data Administration Newsletter (TDAN). Available online: https://tdan.com/data-vault-series-1-data-vault-overview/5054 (accessed on 5 April 2025)

Dip Bharatbhai Patel. (2025). Leveraging BI for Competitive Advantage: Case Studies from Tech Giants. Frontiers in Emerging Engineering & Technologies, 2(04), 15–21. Retrieved from https://irjernet.com/index.php/feet/article/view/166

Khan RU, Richardson C, Salamzadeh Y. Spurring competitiveness, social and economic performance of family-owned SMEs through social entrepreneurship; a multi-analytical SEM & ANN perspective. Technol Forecast Soc Chang. 2022. https://doi.org/10.1016/j.techfore.2022.122047.

Peters MD, Wieder B, Sutton SG, Wakefield J. Business intelligence systems use in performance measurement capabilities: implications for enhanced competitive advantage. Int J Account Inf Syst. 2016;21:1–17. https://doi.org/10.1016/j.accinf.2016.03.001.

Wang Z, Li M, Lu J, Cheng X. Business Innovation based on artificial intelligence and Blockchain technology. Inf Process Manag. 2022. https://doi.org/10.1016/j.ipm.2021.102759.

Verma N, Sharma V. Sustainable competitive advantage by implementing lean manufacturing a case study for Indian SME. Mater Today Proc. 2017;4(8):9210–7. https://doi.org/10.1016/j.matpr.2017.07.279.

Kumar A, Kalse A. Usage and adoption of artificial intelligence in SMEs. Mater Today Proc. 2022. https://doi.org/10.1016/j.matpr.2021.01.595.

Marcucci G, Ciarapica F, Poler R, Sanchis R. A bibliometric analysis of the emerging trends in silver economy. IFAC-PapersOnLine. 2021;54(1):936–41. https://doi.org/10.1016/J.IFACOL.2021.08.190.

Xie L, Chen Z, Wang H, Zheng C, Jiang J. Bibliometric and visualized analysis of scientific publications on atlantoaxial spine surgery based on web of science and VOSviewer. World Neurosurg. 2020;137:435-442.e4. https://doi.org/10.1016/J.WNEU.2020.01.171.