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Abstract

Investigations into the Use of AI Technology in Conventional Business Intelligence Systems

Krishna Gupta

Vivekananda Institute of Professional Studies, New Delhi

150-155 Vol: 13, Issue: 1, 2023
Receiving Date: 2022-12-30
Acceptance Date: 2023-01-23
Publication Date: 2023-03-21
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http://doi.org/10.37648/ijtbm.v13i01.013

Abstract

This paper gives a detailed study of the main difficulties and limitations of traditional BI (Business Intelligence) systems. It combines the newest AI technology to prove the viability of employing Artificial Intelligence (AI) technology in traditional BI systems. The efficiency, calibre, and depth of data analysis can be enhanced by integrating AI with BI, supporting business development and decision-making for organisations in the big data era.

Keywords: Business Intelligence; AI technology; organisations

References

  1. Wang, Jian, et al. 'A survey on artificial intelligence-driven business intelligence.' International Journal of Computer Applications 177.1 (2018): 1-7.
  2. Mesiya, Mark, et al. 'Recent advances in AI and machine learning in business intelligence and analytics.' Procedia Computer Science 125 (2017): 216-223.
  3. Oussous, Ahmed, et al. 'Big health data analytics: challenges and opportunities.' Journal of King Saud University-Computer and Information Sciences 32.4 (2020): 395-405.
  4. Nguyen, Quoc Huy, et al. 'Artificial intelligence in business: progress, best practice, and future challenges.' Electronic Journal of Applied Statistical Analysis 10.2 (2017): 595-612.
  5. Sivarajah, U., Kamal, M. M., Irani, Z., & Weerakkody, V. (2017). Critical analysis of Big Data challenges and analytical methods. Journal of Business Research, 70, 263-286.
  6. Marr, B. (2019). How artificial intelligence is revolutionizing business in 2019. Forbes.
  7. Wang, F., Bandar, Z., & McLean, D. (2016). Business intelligence and analytics: from big data to big impact. MIS Quarterly, 40(4), 1165-1188.
  8. Shrestha, R., & Mahmood, A. N. (2018). Artificial intelligence and business analytics. Business Horizons, 61(6), 829-838.
  9. Taulli, T. (2019). AI: Its Impact on Business. AI and Machine Learning for Business: A No-Nonsense Guide to Data-Driven Technologies, 25-45.
  10. Davenport, T. H., Gu, Q., Jin, J., & Reinhart, A. (2018). Artificial Intelligence for the Real World. Harvard Business Review, 96(1), 108- 116. 190
  11. Sunil Kumar Sehrawat. Intelligent Healthcare Management: Advancing Healthcare with Integrated AI and ML Solutions (2017), vol-17
  12. Venkata SK Settibathini. Strategic analysis review of data analytics with the help of artificial intelligence.2023, Vol-26,1-10.
  13. Gopichand Vemulapalli, Self-Service Analytics Implementation Strategies for Empowering Data Analysts.2023, Vol-4,1-14.
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