Strategies for Successful Data Migration in Large-Scale Enterprise Systems: Addressing Performance, Security, and Compatibility

Abstract

Data migration in large-scale enterprise systems presents critical challenges, particularly in performance, security, and compatibility when transitioning to modern data architectures. This paper investigates strategies to overcome these challenges, with an emphasis on pre-migration planning, which involves assessing the current data landscape, identifying dependencies, and selecting the appropriate target architecture. Data validation and transformation are crucial to ensure that data is accurate, complete, and compatible with the new system. Security remains a top priority, with recommendations for encryption, access control, and data masking to safeguard sensitive information during the migration process. Post-migration testing and optimization are essential to confirm successful migration and guarantee that the new system functions efficiently. The paper concludes that a strategic, well-executed migration plan is vital to minimizing downtime, protecting data integrity, and achieving the advantages of modern architectures. Careful planning, strong security protocols, and rigorous testing enable organizations to execute seamless migrations that align with long-term business goals.