Next Generation Cloud Intelligence Frameworks for Secure Data Engineering and Adaptive Analytics
DOI:
https://doi.org/10.15680/IJCTECE.2026.0902019Keywords:
Cloud intelligence, secure data engineering, adaptive analytics, cloud computing, machine learning, data security, real-time analytics, data governance, distributed systems, intelligent frameworksAbstract
The exponential growth of data and the increasing reliance on cloud computing have transformed how organizations manage, process, and analyze information. Next-generation cloud intelligence frameworks are emerging as critical enablers for secure data engineering and adaptive analytics in modern enterprise ecosystems. These frameworks integrate advanced technologies such as artificial intelligence (AI), machine learning (ML), and distributed computing to enhance data processing capabilities while ensuring robust security and governance. This research explores the design and implementation of intelligent cloud frameworks that support secure data pipelines, real-time analytics, and adaptive decision-making. Emphasis is placed on data protection mechanisms, including encryption, access control, and anomaly detection, to mitigate evolving cyber threats. Additionally, the study highlights the role of adaptive analytics in enabling systems to dynamically respond to changing data patterns and business requirements. Despite their potential, these frameworks face challenges such as integration complexity, data privacy concerns, and scalability constraints. The proposed framework aims to address these limitations by incorporating modular architectures and intelligent automation. This research contributes to the advancement of cloud-based data intelligence by providing insights into building secure, scalable, and adaptive systems for future enterprise applications.
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