Vol. 4 No. 1 (2024): Journal of AI-Assisted Scientific Discovery
Articles

Advancing Business Intelligence with Big Data and AI: The Convergence of Customer Insights and Predictive Analytics for Competitive Advantage

Giulia Bianchi
Associate Professor, Biomedical Informatics Department, Venezia Institute of Technology, Venice, Italy
Cover

Published 10-01-2024

Keywords

  • Business Intelligence,
  • Big Data,
  • Artificial Intelligence,
  • Predictive Analytics,
  • Customer Insights,
  • Competitive Advantage,
  • Predictive Modeling
  • ...More
    Less

How to Cite

[1]
G. Bianchi, “Advancing Business Intelligence with Big Data and AI: The Convergence of Customer Insights and Predictive Analytics for Competitive Advantage”, Journal of AI-Assisted Scientific Discovery, vol. 4, no. 1, pp. 1–17, Jan. 2024, Accessed: Sep. 18, 2024. [Online]. Available: https://scienceacadpress.com/index.php/jaasd/article/view/7

Abstract

In today's rapidly evolving digital landscape, the convergence of big data and artificial intelligence (AI) has revolutionized business intelligence (BI), enabling organizations to extract actionable insights from vast volumes of customer data. This paper explores the synergy between big data and AI in BI, focusing on advanced analytics techniques like predictive modeling, machine learning, and sentiment analysis. By leveraging these techniques, businesses can gain a competitive advantage in Industry 4.0 by understanding customer behavior, preferences, and trends more comprehensively than ever before. This research underscores the importance of integrating big data and AI in BI strategies to unlock the full potential of customer insights and drive strategic decision-making.

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References

  1. Chen, Han. "The Application of Big Data in Business Intelligence: A Literature Review." Journal of Business and Retail Management Research, vol. 11, no. 2, 2017, pp. 140-145.
  2. Reddy, Surendranadha Reddy Byrapu, and Surendranadha Reddy. "Large Scale Data Influences Based on Financial Landscape Using Big Data." Tuijin Jishu/Journal of Propulsion Technology 44.4 (2023): 3862-3870.
  3. Davenport, Thomas H. "Competing on Analytics." Harvard Business Review, vol. 84, no. 1, 2006, pp. 98-107.
  4. Gupta, Vijay, and Hui Xiong. "Big Data Analytics in Business Intelligence and Marketing." Journal of Management Analytics, vol. 2, no. 4, 2015, pp. 283-295.
  5. Hsu, Yu-Chin, et al. "The Application of Artificial Intelligence in Business Intelligence: A Systematic Review." Journal of Enterprise Information Management, vol. 32, no. 7, 2019, pp. 1261-1281.
  6. Li, Xiujin, et al. "A Review of Big Data Analytics and Its Application in Business Intelligence." Journal of Industrial Integration and Management, vol. 4, no. 4, 2019, pp. 289-298.
  7. Marjanović, Olivera, et al. "The Role of Predictive Analytics in Business Intelligence." TEM Journal, vol. 10, no. 4, 2021, pp. 1714-1720.
  8. Murphy, Kevin P. Machine Learning: A Probabilistic Perspective. MIT Press, 2012.
  9. Provost, Foster, and Tom Fawcett. Data Science for Business: What You Need to Know About Data Mining and Data-Analytic Thinking. O'Reilly Media, 2013.
  10. Ransbotham, Sam, and David Kiron. "The Age of Analytics: Competing in a Data-Driven World." MIT Sloan Management Review, vol. 59, no. 4, 2018, pp. 1-25.
  11. Sharma, Ruchi, and Mohit Kumar. "The Evolution of Artificial Intelligence in Business Intelligence." International Journal of Computer Applications, vol. 144, no. 9, 2016, pp. 1-4.
  12. Smith, Marc. "Predictive Analytics: The Future of Business Intelligence." Forbes, 12 Mar. 2019, www.forbes.com/sites/forbestechcouncil/2019/03/12/predictive-analytics-the-future-of-business-intelligence/?sh=15e7c1c85612.
  13. Spathis, Charalampos T., and George Pantazopoulos. "Artificial Intelligence in Business Intelligence: A Bibliometric Analysis." European Journal of Business Science and Technology, vol. 7, no. 2, 2021, pp. 107-115.
  14. Tan, Pang-Ning, et al. Introduction to Data Mining. Pearson, 2005.
  15. Thota, Chandrasekhar, and Vipul Gupta. "Big Data Analytics and Business Intelligence." International Journal of Computer Applications, vol. 160, no. 7, 2017, pp. 1-5.
  16. Turban, Efraim, et al. Business Intelligence: A Managerial Perspective on Analytics. Pearson, 2019.
  17. Wang, Kai, et al. "Big Data Analytics in Business Intelligence: An Overview." Big Data Research, vol. 18, 2020, article 100144.
  18. Alghayadh, Faisal Yousef, et al. "Ubiquitous learning models for 5G communication network utility maximization through utility-based service function chain deployment." Computers in Human Behavior (2024): 108227.
  19. Dutta, Ashit Kumar, et al. "Deep learning-based multi-head self-attention model for human epilepsy identification from EEG signal for biomedical traits." Multimedia Tools and Applications (2024): 1-23.
  20. Raparthi, Mohan, Sarath Babu Dodda, and Srihari Maruthi. "AI-Enhanced Imaging Analytics for Precision Diagnostics in Cardiovascular Health." European Economic Letters (EEL) 11.1 (2021).
  21. Kulkarni, Chaitanya, et al. "Hybrid disease prediction approach leveraging digital twin and metaverse technologies for health consumer." BMC Medical Informatics and Decision Making 24.1 (2024): 92.
  22. Raparthi, Mohan. "Biomedical Text Mining for Drug Discovery Using Natural Language Processing and Deep Learning." Dandao Xuebao/Journal of Ballistics 35
  23. Kumar, Mungara Kiran, et al. "Approach Advancing Stock Market Forecasting with Joint RMSE Loss LSTM-CNN Model." Fluctuation and Noise Letters (2023).
  24. Sati, Madan Mohan, et al. "Two-Area Power System with Automatic Generation Control Utilizing PID Control, FOPID, Particle Swarm Optimization, and Genetic Algorithms." 2024 Fourth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT). IEEE, 2024.
  25. Raparthy, Mohan, and Babu Dodda. "Predictive Maintenance in IoT Devices Using Time Series Analysis and Deep Learning." Dandao Xuebao/Journal of Ballistics 35: 01-10.
  26. Weiss, Sholom M., and Nitin Indurkhya. Predictive Data Mining: A Practical Guide. Morgan Kaufmann, 2010.
  27. Wu, Xiaolin, et al. "An Overview of Predictive Analytics in Business Intelligence Applications." IEEE Access, vol. 8, 2020, pp. 23798-23814.
  28. Yan, Zhiping, et al. "A Bibliometric Analysis on Business Intelligence Research." International Journal of Information Management, vol. 41, 2018, pp. 28-39.
  29. Zhang, Weishan, et al. "Deep Learning in Business Intelligence and Analytics: A Survey." Journal of Management Analytics, vol. 7, no. 1, 2020, pp. 17-40.