International Journal of Knowledge Content Development & Technology

Research Institute for Knowledge Content Development & Technology (건국대학교 지식콘텐츠연구소)
권호 표지
DOI QR코드

DOI QR Code

Unlocking Digital Transformation: The Pivotal Role of Data Analytics and Business Intelligence Strategies

  • Edwin Omol (Department of Computing and Informatics, Kenya Highlands University) ;
  • Lucy Mburu (Department of Networks and Applied Computing (NAC), School of Technology, KCA University) ;
  • Paul Abuonji (KCA University)
  • Received : 2023.09.19
  • Accepted : 2024.05.01
  • Published : 2024.09.30
Download PDF
⟨ Previous Next ⟩

Abstract

This article aims to comprehensively analyze the crucial role played by data analytics and business intelligence (BI) strategies in propelling digital transformation within diverse industries. Through an extensive literature review and examination of real-world case studies, the study employs a systematic analysis of scholarly works and industry reports. This approach provides a panoramic view of how organizations utilize data-driven insights for competitive advantages, improved customer experiences, and fostering innovation. The findings underscore the pivotal significance of data analytics and BI strategies in influencing strategic decision-making, enhancing operational efficiency, and ensuring long-term sustainability across various industries. The study stands out in its originality by offering a unique synthesis of insights derived from scholarly works and real-world case studies, contributing to a holistic understanding of the transformative impact of data analytics and BI on contemporary business practices. While the study provides valuable insights, limitations include the scope of available literature and case studies. The implications call for further research to explore emerging trends and evolving challenges in the dynamic landscape of data analytics and BI. The practical implications highlight the tangible benefits organizations can derive from integrating data analytics and BI strategies, emphasizing their role in shaping strategic decisions and fostering operational efficiency. In a broader context, the study delves into the social implications of the symbiotic relationship between data analytics, BI, and digital transformation. It explores how these strategies impact broader societal and economic aspects, influencing innovation and sustainability.

Keywords

Acknowledgement

We are grateful to the researchers, scholars, and authors whose work we have referenced in this paper.

References

  1. Almazmomi, N., Ilmudeen, A., & Qaffas, A. A. (2022). The impact of business analytics capability on data-driven culture and exploration: achieving a competitive advantage. Benchmarking: An International Journal, 29(4), 1264-1283.
  2. Ammanath, B. (2022). Trustworthy AI: a business guide for navigating trust and ethics in AI. John Wiley & Sons.
  3. Bi, Z., Jin, Y., Maropoulos, P., Zhang, W. J., & Wang, L. (2023). Internet of things (IoT) and big data analytics (BDA) for digital manufacturing (DM). International Journal of Production Research, 61(12), 4004-4021.
  4. Bonesso, S., Bruni, E., Gerli, F., Bonesso, S., Bruni, E., & Gerli, F. (2020). How big data creates new job opportunities: Skill profiles of emerging professional roles. Behavioral Competencies of Digital Professionals: Understanding the Role of Emotional Intelligence, 21-39.
  5. Co-Learner. (2022, November 19). 4 Types of Data Analytics Every Analyst should Know-Descriptive, Diagnostic, Predictive, Prescriptive. Medium. https://medium.com/co-learning-lounge/types-of-data-analytics-descriptive-diagnostic-predictive-prescriptive-922654ce8f8f
  6. Davenport, T. H. (2018). The AI Advantage: How to put the artificial intelligence revolution to work. MIT Press.
  7. Dolezel, D., & McLeod, A. (2019). Big data analytics in healthcare: Investigating the diffusion of innovation. Perspectives in health information management, 16 (Summer).
  8. Foltean, F. S., & van Bruggen, G. H. (2022). Digital Technologies, Marketing Agility, and Marketing Management Support Systems: How to Remain Competitive in Changing Markets. In Organizational Innovation in the Digital Age (pp. 1-38). Cham: Springer International Publishing.
  9. Geradin, D., Karanikioti, T., & Katsifis, D. (2021). GDPR Myopia: how a well-intended regulation ended up favouring large online platforms-the case of ad tech. European Competition Journal, 17(1), 47-92.
  10. Horani, O. M., Khatibi, A., AL-Soud, A. R., Tham, J., & Al-Adwan, A. S. (2023). Determining the Factors Influencing Business Analytics Adoption at Organizational Level: A Systematic Literature Review. Big Data and Cognitive Computing, 7(3), 125.
  11. Kharakhash, O. (2023). Data Visualization: Transforming Complex Data into Actionable Insights. Automation of Technological & Business Processes/Avtomatizacia Tehnologiceskih i Biznes-Processov, 15(2).
  12. Masakala, C., Omol, E., Wauyo, F., & Okumu, J. (2017). The role of budgeting process in financial performance: A case study of Bugisu Cooperative Union ltd Mbale, Uganda. American Journal of Finance, 1(5), 31-48.
  13. Miller, R., & Fang, A. (2023). Business Intelligence Leveraging Regression Models, Artificial Intelligence, Business Intelligence and Strategy. Artificial Intelligence, Business Intelligence and Strategy (May 14, 2023).
  14. Nguyen, P., & Mogaji, E. (2023). Digital strategies for aiding ease of decision-making in services sector.
  15. Omol E., Mburu L., & Abuonji P. (2024b). Pioneering digital transformation in Africa: the path to maturity amidst unique challenges and opportunities. Can. J. Bus. Inf. Stud., 6(2), 35-48. https://doi.org/10.34104/cjbis.024.035048
  16. Omol, E. J. (2023). Organizational digital transformation: from evolution to future trends. Digital Transformation and Society, Vol. ahead-of-print No. ahead-of-print.
  17. Omol, E. J., Ogalo, J. O., Abeka, S. O., & Omieno, K. K. (2016). Mobile Money Payment Acceptance Model in Enterprise Management: A Case Study of MSE's in Kisumu City, Kenya. Mara Research Journal of Information Science & Technology, 1, 1-12.
  18. Omol, E., & Ondiek, C. (2021). Technological Innovations Utilization Framework: The Complementary Powers of UTAUT, HOT-Fit Framework and; DeLone and McLean IS Model. International Journal of Scientific and Research Publications (IJSRP), 11(9), 146-151.
  19. Omol, E., Abeka, S., & Wauyo, F. (2017). Factors Influencing Acceptance of Mobile money Applications in Enterprise Management: A Case Study of Micro and Small Enterprise Owners in Kisumu Central Business District, Kenya. IJARCCE, 6, 208-219.
  20. Omol, E., Abeka, S., & Wauyo, F. (2017a). Factors influencing acceptance of mobile money applications in enterprise management: A case study of micro and small enterprise owners in kisumu central business district, Kenya. International Journal of Advanced Research in Computer and Communication Engineering, 6(1), 208-219.
  21. Omol, E., Mburu, L., & Abuonji, P. (2023). Digital Maturity Action Fields for SMEs in Developing Economies. Journal of Environmental Science, Computer Science, and Engineering & Technology, 12(3).
  22. Omol, E., Mburu, L., & Onyango, D. (2024). Anomaly Detection in IoT Sensor Data Using Machine Learning Techniques For Predictive Maintenance In Smart Grids. International Journal of Science, Technology & Management, 5(1), 201-210.
  23. Omol, E., Onyangor, D., Mburu, L., & Abuonji, P. (2024a). Application of K-Means Clustering For Customer Segmentation In Grocery Stores In Kenya. International Journal of Science, Technology & Management, 5(1), 192-200.
  24. Onyango, D. A. (2022). Determinants of Profitability on Street Vending in Kisumu Central Business District, Kenya (Doctoral dissertation, University of Nairobi).
  25. Patil, S. M., Baramati, P., Dhone, N. C., & Chourasiya, R. H. (2023). Industry 4.0 Technologies in The Context of Supply Chain Management 4.0. The Online Journal of Distance Education and e-Learning, 11(2).
  26. Ragazou, K., Passas, I., Garefalakis, A., Galariotis, E., & Zopounidis, C. (2023). Big Data Analytics Applications in Information Management Driving Operational Efficiencies and Decision-Making: Mapping the Field of Knowledge with Bibliometric Analysis Using R. Big Data and Cognitive Computing, 7(1), 13.
  27. Rud, O. P. (2009). Business intelligence success factors: tools for aligning your business in the global economy (Vol. 18). John Wiley & Sons.
  28. Shao, C., Yang, Y., Juneja, S., & GSeetharam, T. (2022). IoT data visualization for business intelligence in corporate finance. Information Processing & Management, 59(1), 102736.
  29. Team, E. (2023, July 23). Business intelligence and data mining capabilities benefits. ExistBI - Uniting Business & Technology. https://www.existbi.com/blog/business-intelligence-systems-and-data-mining/
  30. Wauyo, F., Omol, E., & Okumu, J. (2017). Effectiveness of Business Intelligence Technology Absorptive Capacity and Innovation Competency of University Staff, Case of Uganda Christian University Mbale Campus. European Journal of Technology, 1(2), 55-73.
  31. Yang, B., Liu, Y., & Chen, W. (2023). A twin data-driven approach for user-experience-based design innovation. International Journal of Information Management, 68, 102595.
  32. Yangzom, T., & Ahuja, L. (2023, July). Uses of Big Data to Understand Consumers' Buying Behavior. In 2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC) (pp. 819-823). IEEE.