Enterprise context is different nowadays, and the process of regulating and migrating petabyte-scale data between heterogeneous systems is no longer an exception; it is a rather standard practice. Inspired by adopting cloud environments, modernization of the platforms, or legal changes, the demand for an effective, reliable, and sustainable cross-system data migration methodology has become a burning issue. The architectural underpinnings, implementations, performance stipulations, and transitive obstacles of the implementation of large-scale data migration across various environments and properties, including cloud data warehouses, legacy systems, and real-time platforms, are discussed in this review. The review uses the analysis of the current practice and case studies to analyze the state-of-the-art frameworks and find gaps in the current methodology. It ends by moving forward to explore automation, security, explainability, and sustainability within next-gen data migration ecosystems.
Rajesh Sura (Wed,) studied this question.