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Discover how to build a scalable Model Factory framework for operationalizing machine learning in this 45-minute conference talk by Nihan Yami from SAS Institute, presented at the Data Science Festival Game On event 2025. Learn practical strategies for transitioning ML models from development to production efficiently through real-world insights from implementing a Model Factory within Revenue Operations (RevOps). Explore the implementation of feature stores to enhance model efficiency and enable reusability across different models, while mastering best practices for monitoring both data drift and model drift. Gain actionable knowledge on the critical role of business analysis principles in designing scalable AI solutions, understand how feature stores accelerate model development and ensure consistency, and discover proven strategies for monitoring and mitigating model drift in fast-paced business environments. Benefit from lessons learned through actual implementation experience, including common pitfalls to avoid when operationalizing AI systems at scale. This introductory-level session provides practical, theory-grounded insights that data science professionals can immediately apply to improve ML operationalization in their organizations, focusing on real-world challenges and proven solutions rather than theoretical concepts.
