Data Validation: A Complex Challenge in Modern AI Systems
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Data Validation: A Complex Challenge in Modern AI Systems
Vishakha Agrawal vishakha.research.id@gmail.com
Abstract—Ensuring the integrity and quality of data is paramount in machine learning (ML) systems, as it directly impacts the reliability and performance of AI models. This paper provides an in-depth examination of the crucial role of data validation in ML pipelines, highlighting the complexities, methodologies, and best practices for guaranteeing data quality. A comprehensive analysis of traditional validation approaches is presented, alongside a discussion of emerging techniques and innovations in the field. Furthermore, this research proposes a novel framework for implementing robust and comprehensive data validation in production ML environments, ultimately en- hancing the trustworthiness and efficacy of modern AI systems.
Keywords - Data Validation, Schema validation, Statistical Validation, Data Drift, Meta-learning