Enterprise Data Migration Strategies for High-Assurance Information Systems

Abstract

Enterprise data migration is one of the essential parts of digital transformation strategies in the development and implementation of high-assurance information systems (HAIS), which include various fields such as healthcare services, defense systems, financial services, and smart manufacturing. The HAIS must meet specific data security, availability, and compliance requirements. However, traditional data migration approaches cannot meet these expectations because they cannot perform real-time validation, risk mitigation, and zero-downtime execution. This paper presents a novel AI-aided data migration framework that focuses on HAIS. The framework is based on the integration of pre-migration intelligence, secure execution, real-time validation, risk mitigation, and post-migration. Advanced technologies such as artificial intelligence and machine learning are used in data migration. Blockchain is also used to ensure data auditability. Additionally, digital twins are employed to ensure data validation. Adaptive data migration strategies such as hybrid and incremental approaches are also included in the framework. This paper presents a novel data migration model based on compliance-centric and risk-centric data migration. This model allows organizations to ensure reliable data migration. The paper proves that the integration of intelligent automation and real-time validation can significantly improve data migration accuracy.