Adaptive Migration–Driven Cloud and Big-Data Enablement for Secure and Scalable SME Analytics
Centralized data operations are often using in Small and medium-sized enterprises (SMEs) for easy data management, but there suffering from few limitations like cloud platform integration with bigdata yet many still face difficulties integrating cloud platforms with big-data capabilities in a scalable and governed manner. To address the problems, this communication presents an Adaptive Cloud -Big-Data Enablement Framework (ACBDEF), which is a realistic mechanism of SME digital data transformation. This framework consists of five main steps, which are technological infrastructure, data governance and compliance, organizational capability development, environmental alignment, and intelligence/value extraction into a common architecture. One of the key elements in this work is the Adaptive Migration Engine (AME) which is used to assess dynamically workloads, the parameters such as data characteristics, regulatory constraints, the cost-performance metrics are used to decide on the optimal deployment in cloud premises, or in hybrid environments. The adaptive decision process is beneficial in assisting SMEs in mitigating technical and organizational issues in enhancing the efficiency, security, and analytical responsiveness. The proposed mechanism brings into line theoretical adoption factors with actionable implementation which provides a structured model for supporting SMEs to achieve sustainable and data-driven cloud transformation.