Advanced International Journal of Multidisciplinary Research

E-ISSN: 2584-0487

An Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 2 Issue 6 November-December 2024 Submit your research before last 3 days of December to publish your research paper in the issue of November-December.
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Volume 2 Issue 6
November-December 2024

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Quantum Machine Learning for Advanced Data Processing in Business Analytics: A Path Toward Next-Generation Solutions

Author(s) Shifa Sarkar, Umesh Khadka, Sarowar Hossain, Nahid Khan
Country United States
Abstract Quantum Machine Learning (QML) is a rising paradigm of computing that holds high possibilities to revolutionise data analysis in the business analytics industry. This paper aims at presenting how QML can solve the increasingly challenging demands of big contributions to large-scale data analysis in business contexts, achieving better performance than orthodox machine learning methods in terms of time and efficacy. LIQUID: This research utilises actual business data and scenarios and solving problems by using quantum algorithms – VQE and QSVM. At the core of our approach, we perform extensive validation of QML models on platforms such as IBM’s Quantum Experience and D-Wave systems pertaining to critical use cases for businesses would include financial modelling, supply chain management, and customer behaviour prediction. The results presented here suggest that quantum algorithm speeds processing by 30-50% when compared with conventions approaches of computation. Moreover, QML has shown better results for prediction in analytics for various firms and provide them better aptitudes for decision-making. Hence the uniqueness of this research by grounding real world business problems in quantum algorithms and demonstrating empirically how superior they are compared to the classical alternatives in dealing with large datasets. Considering the future of business analytics, QML looks set to be a real game changer for industries that heavily rely on big data analysis. In this it has filled a gap which would cause a scholarly without hard gap between theoretical quantum computing and real business applications.
Keywords Quantum Machine Learning, Business Analytics, Quantum Computing, Data Processing, Artificial Intelligence
Discipline Other
Published In Volume 2, Issue 5, September-October 2024
Published On 2024-10-22
Cite This Quantum Machine Learning for Advanced Data Processing in Business Analytics: A Path Toward Next-Generation Solutions - Shifa Sarkar, Umesh Khadka, Sarowar Hossain, Nahid Khan - AIJMR Volume 2, Issue 5, September-October 2024. DOI 10.62127/aijmr.2024.v02i05.1107
DOI https://doi.org/10.62127/aijmr.2024.v02i05.1107
Short DOI https://doi.org/g8nr87
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