STM Journals Peer-reviewed research from Consortium e-Learning Network

3 publications

  • Published Subscription Review Article

    Ensuring Data Traceability Across Multiple Cloud Environments

    By Anil Kumar Bayya

    Abstract: This study investigates the challenges and solutions for ensuring data traceability across multiple cloud environments. With organizations' increasing reliance on cloud infrastructure, maintaining data traceability is crucial for compliance, data integrity, and secure data management. The diversity of cloud systems, spanning public, private, and hybrid models, introduces complexities in tracking data lineage, access, and movement. This study delves into multi-cloud strategies' technical and operational hurdles, such as varying data formats, …

    Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 08–22 Read article

  • Published Subscription Review Article

    Utilizing AWS Advanced Services for Modernizing and Refactoring Legacy Systems to Achieve Cloud-Native Capabilities

    By Anil Kumar Bayya

    Abstract: Updating and restructuring outdated systems is essential for organizations seeking to harness the scalability, adaptability, and robustness offered by cloud-native architectures. Legacy systems can obstruct innovation because of their rigid structure, expensive maintenance, and inability to scale effectively. Amazon Web Services (AWS) provides a comprehensive suite of advanced services that enable the efficient transformation of such systems into modern, cloud-native solutions. This paper explores strategies and best practices for utilizing …

    Published in Recent Trends in Parallel Computing · Vol. 12, Issue 1, 2025 · pp. 44–65 Read article

  • Published Subscription Original Research

    Data-Driven Predictive Analytics and Decision- Making in FinTech Using MongoDB and High-Throughput Data Pipelines

    By Anil Kumar Bayya

    Abstract: This paper examines the implementation of MongoDB and high-throughput data pipelines within the financial technology (FinTech) sector to drive data-informed predictive analytics and decision-making. The study focuses on the architectural components, scalability, and challenges of integrating NoSQL databases into real-time data ingestion and analytics pipelines. The transformative potential of these technologies in modern financial systems is highlighted through practical use cases such as fraud detection, credit scoring, and personalized financial …

    Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 1–15 Read article

Support