Abstract

Migrating legacy systems to next-generation data architectures is a complex but necessary process for organizations aiming to enhance operational efficiency, scalability, and technological innovation. This paper proposes a comprehensive framework for migrating legacy systems to modern data architectures, ensuring seamless integration and scalability. The framework builds on existing migration methodologies by incorporating advanced techniques for mapping, grouping, and prioritizing legacy systems, aligning with contemporary business goals and future growth strategies. The framework begins with a thorough assessment of the existing legacy infrastructure, mapping each system’s data structure, processes, and dependencies. This mapping provides a clear understanding of the systems that require transformation, as well as those that can be retained, modernized, or replaced. The next step involves grouping systems based on factors such as business criticality, technological compatibility, and resource availability. This segmentation enables a more structured approach to migration, ensuring that the most critical systems are prioritized, thus minimizing disruption to ongoing operations. Prioritization is key to successful migration, and the framework outlines a systematic process for ranking legacy systems based on their potential impact on performance, scalability, and alignment with the new data architecture. The use of AI-driven tools for predictive analytics further refines the prioritization process by forecasting the outcomes of migrating specific systems. Once systems are mapped, grouped, and prioritized, the framework emphasizes ensuring seamless integration with the new data architecture. This is achieved through the adoption of modular, scalable cloud-based solutions that support the incremental migration of data and functionalities. The framework also emphasizes the importance of data integrity, security, and compliance throughout the migration process. This research highlights the importance of strategic planning and systematic execution in legacy system migration. By focusing on mapping, grouping, and prioritizing, organizations can achieve a smoother transition to next-generation architectures while minimizing risk and maximizing operational efficiency.