Big Data Platforms and Cloud-Based Analytics for Enterprise Digital Transformation in Saudi Vision 2030

References

[1] Alamri, N., & Alzahrani, S. (2024). Navigating the clouds: An exploratory research of cloud computing adoption in Saudi Arabia's small and medium enterprises. Engineering, Technology & Applied Science Research, 14(6), 17859–17869. https://doi.org/10.48084/etasr.8435

[2] Alghamdi, N., & Aboalela, R. (2023). The impact of cloud computing on firms: A case study of cloud adoption in Saudi Airline Navigation Services Company. Journal of King Abdulaziz University: Computing and Information Technology Sciences, 12(1), 1–12. https://doi.org/10.4197/Comp.12-1.1

[3] Alismaili, S. Z., Li, M., Shen, J., Huang, P., He, Q., & Zhan, W. (2020). Organisational-level assessment of cloud computing adoption: Evidence from the Australian SMEs. Journal of Global Information Management, 28(2), 73–89. https://doi.org/10.4018/JGIM.2020040104

[4] Almatrafi, A. M., & Alharbi, Z. H. (2023). The impact of web analytics tools on the performance of small and medium enterprises. Engineering, Technology & Applied Science Research, 13(5), 11753–11762. https://doi.org/10.48084/etasr.6261

[5] Almulhim, A. F. (2021). Smart supply chain and firm performance: The role of digital technologies. Business Process Management Journal, 27(5), 1353–1372. https://doi.org/10.1108/BPMJ-12-2020-0573

[6] AlNuaimi, B. K., Khan, M., & Ajmal, M. M. (2021). The role of big data analytics capabilities in greening e-procurement: A higher order PLS-SEM analysis. Technological Forecasting and Social Change, 169, 120808. https://doi.org/10.1016/j.techfore.2021.120808

[7] Alqahtani, M., Beloff, N., & White, M. (2023). A new adoption of cloud computing model for Saudi Arabian SMEs (ACCM-SME). In K. Arai (Ed.), Intelligent Systems and Applications (Lecture Notes in Networks and Systems, Vol. 542, pp. 192–210). Springer. https://doi.org/10.1007/978-3-031-16072-1_15

[8] Awan, U., Shamim, S., Khan, Z., Ul Zia, N., Shariq, S. M., & Khan, M. N. (2021). Big data analytics capability and decision-making: The role of data driven insight on circular economy performance. Technological Forecasting and Social Change, 168, 120766. https://doi.org/10.1016/j.techfore.2021.120766

[9] Bhatti, S. H., Ahmed, A., Ferraris, A., Wan Hussain, W. M. H., & Wamba, S. F. (2025). Big data analytics capabilities and MSME innovation and performance: A double mediation model of digital platform and network capabilities. Annals of Operations Research, 350, 729–752. https://doi.org/10.1007/s10479-022-05002-w

[10] Ciampi, F., Demi, S., Magrini, A., Marzi, G., & Papa, A. (2021). Exploring the impact of big data analytics capabilities on business model innovation: The mediating role of entrepreneurial orientation. Journal of Business Research, 123, 1–13. https://doi.org/10.1016/j.jbusres.2020.09.023

[11] Hai, R., Koutras, C., Quix, C., & Jarke, M. (2023). Data lakes: A survey of functions and systems. IEEE Transactions on Knowledge and Data Engineering, 35(12), 12571–12590. https://doi.org/10.1109/TKDE.2023.3270101

[12] Jayeola, O., Sidek, S., Rahman, A. A., Mahomed, A. S. B., & Hu, J. (2022). Cloud computing adoption in small and medium enterprises (SMEs): A systematic literature review and directions for future research. International Journal of Business and Society, 23(1), 226–243. https://doi.org/10.33736/ijbs.4610.2022

[13] Kostakis, P., & Kargas, A. (2021). Big-data management: A driver for digital transformation? Information, 12(10), 411. https://doi.org/10.3390/info12100411

[14] Liu, Y., Ni, Z., Karlsson, M., & Gong, S. (2021). Methodology for digital transformation with Internet of Things and cloud computing: A practical guideline for innovation in small- and medium-sized enterprises. Sensors, 21(16), 5355. https://doi.org/10.3390/s21165355

[15] Makki, A. A., & Alqahtani, A. Y. (2022). Modeling the barriers surrounding digital government implementation: Revealing prospect opportunities in Saudi Arabia. Sustainability, 14(23), 15780. https://doi.org/10.3390/su142315780

[16] Mathrani, S., & Lai, X. (2021). Big data analytic framework for organizational leverage. Applied Sciences, 11(5), 2340. https://doi.org/10.3390/app11052340

[17] Memish, Z. A., Altuwaijri, M. M., Almoeen, A. H., & Enani, S. M. (2021). The Saudi Data & Artificial Intelligence Authority (SDAIA) vision: Leading the Kingdom's journey toward global leadership. Journal of Epidemiology and Global Health, 11(2), 140–142. https://doi.org/10.2991/jegh.k.210405.001

[18] Mikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. (2020). Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities. Information & Management, 57(2), 103169. https://doi.org/10.1016/j.im.2019.05.004

[19] Olabode, O. E., Boso, N., Hultman, M., & Leonidou, C. N. (2022). Big data analytics capability and market performance: The roles of disruptive business models and competitive intensity. Journal of Business Research, 139, 1218–1230. https://doi.org/10.1016/j.jbusres.2021.10.042

[20] Omurgonulsen, M., Ibis, M., Kazancoglu, Y., & Singla, P. (2021). Cloud computing: A systematic literature review and future agenda. Journal of Global Information Management, 29(6), 1–25. https://doi.org/10.4018/JGIM.20211101.oa40

[21] Orero-Blat, M., Palacios-Marqués, D., Leal-Rodríguez, A. L., & Ferraris, A. (2025). Beyond digital transformation: A multi-mixed methods study on big data analytics capabilities and innovation in enhancing organizational performance. Review of Managerial Science, 19(2), 649–685. https://doi.org/10.1007/s11846-024-00768-8

[22] Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71

[23] Peng, Y., & Tao, C. (2022). Can digital transformation promote enterprise performance? From the perspective of public policy and innovation. Journal of Innovation & Knowledge, 7(3), 100198. https://doi.org/10.1016/j.jik.2022.100198

[24] Rajendran, P., Maloo, S., Mitra, R., Chanchal, A., & Aburukba, R. (2023). Comparison of cloud-computing providers for deployment of object-detection deep learning models. Applied Sciences, 13(23), 12577. https://doi.org/10.3390/app132312577

[25] Saudi Vision 2030. (2024). Vision 2030 Annual Report 2024. Kingdom of Saudi Arabia.

[26] Shah, T. R. (2022). Can big data analytics help organisations achieve sustainable competitive advantage? A developmental enquiry. Technology in Society, 68, 101801. https://doi.org/10.1016/j.techsoc.2021.101801

[27] Shahnawaz, M., & Kumar, M. (2025). A comprehensive survey on big data analytics: Characteristics, tools and techniques. ACM Computing Surveys, 57(8), Article 196, 1–33. https://doi.org/10.1145/3718364

[28] Skafi, M., Yunis, M. M., & Zekri, A. (2020). Factors influencing SMEs' adoption of cloud computing services in Lebanon: An empirical analysis using TOE and contextual theory. IEEE Access, 8, 79169–79181. https://doi.org/10.1109/ACCESS.2020.2987331

[29] Yu, W., Zhao, G., Liu, Q., & Song, Y. (2021). Role of big data analytics capability in developing integrated hospital supply chains and operational flexibility: An organizational information processing theory perspective. Technological Forecasting and Social Change, 163, 120417. https://doi.org/10.1016/j.techfore.2020.120417

[30] Zhang, G., Wang, W., & Liang, Y. (2021). Understanding the complex adoption behavior of cloud services by SMEs based on complexity theory: A fuzzy sets qualitative comparative analysis (fsQCA). Complexity, 2021, 5591446. https://doi.org/10.1155/2021/5591446

@article{1722403,
      author = {Adnan Anwar Shaikh},
      title = {Big Data Platforms and Cloud-Based Analytics for Enterprise Digital Transformation in Saudi Vision 2030},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {2},
      pages = {2200-2212},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1722403.pdf},
      abstract = {Saudi Arabia's Vision 2030 has elevated enterprise digital transformation from a standalone IT initiative to a strategic driver of productivity, innovation, service quality, and economic development. Big data platforms and cloud-based analytics enable this shift by combining varied data, scaling analytics, and supporting knowledgeable decision-making. This review integrates evidence from 2020 to 2025 to clarify how these technologies generate enterprise value and the factors influencing adoption in Saudi Arabia. A structured integrative review included 30 peer-reviewed and policy sources, coded by platform architecture, analytics capability, adoption, governance, innovation, and Vision 2030 alignment. The results show that technology investment alone is not sufficient. Value is realized when elastic infrastructure, governed data, analytical skills, digital frameworks, and decision processes operate cohesively. Saudi evidence stresses the importance of organizational readiness, management support, security, skills, regulation, and provider trust. This paper describes a five-layer framework uniting data foundations, cloud platforms, analytics intelligence, organizational capabilities, and measurable business outcomes. Saudi enterprises should approach cloud analytics as an operating model, embedding governance, cybersecurity, cost accountability, interoperability, and workforce development from the outset.},
      keywords = {big data platforms; cloud analytics; enterprise digital transformation; saudi vision 2030; data governance; analytics capability; cloud computing},
      month = {August},
      doi = {https://doi.org/10.64388/IREV10I2-1722403}
  }