Generative AI for Synthetic Data Testing and Validation in SAP Migration Projects
DOI:
https://doi.org/10.63856/ijis/v2i5/00043Keywords:
Generative Artificial Intelligence, Synthetic Data Generation, SAP Migration , Data Testing and Validation, Enterprise Resource Planning (ERP), Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs)Abstract
SAP migration projects can be complex and challenging, involving many steps and requiring careful testing and validation to ensure that the business can operate smoothly and without disruption. Traditionally, the testing relies on production data, which has severe privacy, security and logistics issues. Generative Artificial Intelligence (AI) has proven to be a revolutionary approach that enables the creation of synthetic data that retain the statistical and relational characteristics of production datasets without revealing sensitive information. This paper examines how generative AI models, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer-based models, can be used to test and validate SAP migration projects. The study reviews the various methods for creating synthetic data, metrics for validating it, and examples of its applications, then discusses the benefits and challenges, as well as its potential in enterprise environments.
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