Exploring the Profound Influence of Machine Learning on Business Intelligence: A Comprehensive Review

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Herison Surbakti 1,* Prashaya Fusiripong 1

1. Information and Communication Technology International College, Rangsit University, Lak Hok, Pathumthani, Thailand

* Corresponding author.

DOI: https://doi.org/10.5815/ijieeb.2024.03.01

Received: 7 Jan. 2024 / Revised: 12 Feb. 2024 / Accepted: 10 Mar. 2024 / Published: 8 Jun. 2024

Index Terms

Business Intelligence (BI), Machine Learning (ML), Technology, Supervised Learning, Unsupervised Learning, Algorithm


Businesses nowadays may save a significant amount of money by using technological solutions. It is impossible to deny this when considering the expenses of acquiring and training new personnel. When faced with such difficulties, technology is virtually always able to assist. Business Intelligence/Machine Learning (BI/ML) is an essential tool in today's decision-making process because of the many issues it has created for contemporary business decision-making. A comparative study of regression models, including linear regression, random forests, and gradient boosting, could unravel their effectiveness in predictive analytics within BI. Machine learning contribution in businesses is vital as it has a strong link with business intelligence, and it helps business decision-making in businesses. Without machine learning, business intelligence is not practical while making decisions, as business owners can't make decisions effectively. This paper will comprehensively review the noteworthy contributions of Machine Learning and its Impact on Business Intelligence. Further, it will discuss the challenges and opportunities of machine learning in business intelligence. Finally, the paper will discuss future correspondence about machine learning in businesses.

Cite This Paper

Herison Surbakti, Prashaya Fusiripong, "Exploring the Profound Influence of Machine Learning on Business Intelligence: A Comprehensive Review", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.16, No.3, pp. 1-10, 2024. DOI:10.5815/ijieeb.2024.03.01


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