Transforming Data Analytics with AI for Informed Decision-Making

Page Numbers: 196-215
Published: 2024-09-08
Digital Object Identifier: 10.58578/ijemt.v2i3.3812
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  • Taiwo Abdulahi Akintayo National Centre for Artificial Intelligence and Robotics, Abuja, Nigeria
  • Chadi Paul Federal University of Technology Owerri, Imo State, Nigeria
  • Madumere Chiamaka Queenet Federal Polytechnic Nekede Owerri Imo State, Nigeria
  • Oluchi Anthonia Nnadiekwe Federal Polytechnic Nekede Owerri Imo State, Nigeria
  • Shittu Sarah Victoria University of Ibadan, Nigeria
  • Fakokunde Babatunde David Ladoke Akintola University of Technology, Nigeria
  • Ogundigba Omotunde Joel Federal University of Technology Akure, Nigeria
  • Olowu Innocent Agada Ahmadu Bello University Zaria, Nigeria
  • Egenuka Rhoda Ngozi Federal Polytechnic Nekede Owerri Imo State, Nigeria
  • Ugochukwu Ukeje Arinze Kennesaw State University, Georgia
  • Grace Alele Ojemerenvhie Ambrose Alli University, Ekpoma, Nigeria
  • Adebesin Adedayo Oluwadamilola Obafemi Awolowo University, Nigeria
  • Chinenye Cordelia Nnamani Institute of Management and Technology, Enugu, Nigeria
  • Usman Wasiu Olayinka Ladoke Akintola University of Technology, Nigeria

Abstract

This study delves into how advanced data analytics and artificial intelligence (AI) can work together to enhance decision-making processes. As we navigate today’s data-driven environment, discovering the synergy between these fields is crucial, given the growing complexity of datasets. Advanced analytical tools are essential, and AI offers exceptional capabilities in pattern recognition and automation. This research investigates how cosmbining data analytics techniques—such as Predictive Modeling, Clustering, and Trend Analysis—with AI approaches like Machine Learning and Deep Learning can improve decision-making. A key focus of the study is on making AI models more interpretable and transparent. It emphasizes the importance of ensuring that AI-driven decisions are clear and understandable. Additionally, the research addresses ethical considerations and the need for human-centered design, aiming to balance AI’s power with openness. It also strives for responsible AI use by tackling issues such as bias and promoting ethical practices in the application of advanced data analytics and AI. The study demonstrates practical applications in areas like healthcare and finance, showing how these technologies can transform personalized medicine, disease prediction, risk assessment, fraud detection, and market trend analysis. Overall, this research highlights the valuable interaction between advanced data analytics and AI, offering a guide for organizations to enhance their decision-making while adhering to ethical standards and responsible AI use.

Keywords: AI; Machine Learning; Predictive Modeling; Data Analytics; Decision Making
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How to Cite
Akintayo, T. A., Paul, C., Queenet, M. C., Nnadiekwe, O. A., Victoria, S. S., David, F. B., Joel, O. O., Agada, O. I., Ngozi, E. R., Arinze, U. U., Ojemerenvhie, G. A., Oluwadamilola, A. A., Nnamani, C. C., & Olayinka, U. W. (2024). Transforming Data Analytics with AI for Informed Decision-Making. International Journal of Education, Management, and Technology, 2(3), 196-215. https://doi.org/10.58578/ijemt.v2i3.3812

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