Digital twin technology for predictive database migration: The future of risk-free data transitions

Digital twin technology offers a transformative solution for one of enterprise IT's most challenging operations: database migrations. By creating virtual replicas of database environments, organizations can simulate migration processes before implementation, significantly reducing risks associated with downtime, data integrity issues, and performance degradation. The integration of artificial intelligence with digital twins enables accurate prediction of migration outcomes, automated detection of potential bottlenecks, and optimization of migration strategies. While implementing digital twins for database migrations presents challenges in synchronization, computational resources, and simulation accuracy, the technology provides unprecedented visibility into migration complexities. As digital twins mature, they promise to evolve database migrations from high-risk events into continuous, seamless processes with minimal business impact, fundamentally changing how organizations approach database modernization and technology transitions.

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Publication Details

Journal
World Journal of Advanced Engineering Technology and Sciences
Published
2025-04-11
DOI
https://doi.org/10.30574/wjaets.2025.15.1.0269
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Digital twin technology for predictive database migration: The future of risk-free data transitions

Ellavarasan Asokan
World Journal of Advanced Engineering Technology and Sciences
Traffic Prediction and Management Techniques
article

Digital twin technology for predictive database migration: The future of risk-free data transitions

Ellavarasan Asokan
article en

Abstract

Digital twin technology offers a transformative solution for one of enterprise IT's most challenging operations: database migrations. By creating virtual replicas of database environments, organizations can simulate migration processes before implementation, significantly reducing risks associated with downtime, data integrity issues, and performance degradation. The integration of artificial intelligence with digital twins enables accurate prediction of migration outcomes, automated detection of potential bottlenecks, and optimization of migration strategies. While implementing digital twins for database migrations presents challenges in synchronization, computational resources, and simulation accuracy, the technology provides unprecedented visibility into migration complexities. As digital twins mature, they promise to evolve database migrations from high-risk events into continuous, seamless processes with minimal business impact, fundamentally changing how organizations approach database modernization and technology transitions.

World Journal of Advanced Engineering Technology and SciencesVol. 15(1)
Openalex Percentile: Top 93%
Traffic Prediction and Management Techniques
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