Advancing E-Commerce Data and Security Frameworks: Novel Approaches for Improved Analytics and Operational Excellence

Authors

  • Tran Quoc Bao Can Tho University, Department of Computer Science, 3/2 Street, Ninh Kieu District, 900000 Can Tho, Vietnam. Author
  • Le Hoang Nam Hanoi University of Industry, Department of Computer Science, 298 Cau Dien Street, Bac Tu Liem, 100000 Hanoi, Vietnam. Author

Abstract

The exponential growth of e-commerce has brought about a myriad of opportunities and challenges, particularly in terms of data analytics, security, and operational efficiency. As digital transactions continue to rise, so do the complexities associated with managing large volumes of data and ensuring secure transactions. Traditional e-commerce frameworks often struggle to meet the demands for enhanced security and robust data analytics, which are critical for operational success and customer trust. This paper presents an in-depth exploration of novel approaches in e-commerce frameworks, focusing on advancements in data analytics techniques and enhanced security mechanisms to facilitate operational excellence. We examine the integration of artificial intelligence (AI) and machine learning (ML) for predictive analytics, customer behavior insights, and operational optimization. Furthermore, the paper discusses state-of-the-art security protocols, including blockchain technology and quantum-resistant encryption, designed to mitigate evolving cybersecurity threats. Additionally, we explore the role of real-time analytics in decision-making processes, highlighting how businesses can leverage instantaneous data to improve inventory management, personalize user experiences, and optimize supply chain logistics. The paper also addresses privacy considerations and compliance with regulations such as GDPR, underscoring the importance of balancing data utility with stringent privacy safeguards. Through a synthesis of recent literature and case studies, we propose a comprehensive framework that integrates these advanced data and security practices into existing e-commerce infrastructures. The proposed framework aims to deliver scalable, secure, and efficient solutions that can enhance both analytics and operational capacities, ultimately driving greater customer satisfaction and competitive advantage. This work contributes to the field by providing actionable insights into the implementation of cutting-edge e-commerce technologies, thus offering a pathway for businesses to achieve sustained growth in an increasingly digitalized marketplace.

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Published

2022-12-10

How to Cite

Advancing E-Commerce Data and Security Frameworks: Novel Approaches for Improved Analytics and Operational Excellence. (2022). International Journal of Data Science and Intelligent Applications, 6(12), 21-33. https://journalgate.com/index.php/IJDI/article/view/22