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Tuesday, April 24, 2018 
01:30 PM - 02:30 PM
Many organizations have interest or initiatives in Machine Learning (ML) and Artificial Intelligence (AI) projects. There are certainly challenges in algorithm and model creation; however, the models produced need a continuous flow of information to learn over time. This presentation gives an overview of how we successfully structured our environment to support a sizeable strategic project, in concert with bringing additional value to our organization by implementing data as a service through data virtualization. Some topics we will address are:
- How do I continuously acquire and deploy data?
- How do I manage big data effectively?
- How do I ensure models can continuously learn?
- How do I position to effectively exploit future data sources?
- How do I handle data protection while working with an external research partner?
- How do I position for reuse of information for self-service and analytics?
- What are some challenges and solutions associated with AI and ML projects?
Terry Moon is the Enterprise Information Architect for McCormick & Company, Inc. Terry is focused on defining McCormick’s standards and architecture for maximizing opportunities in leveraging information through the adoption of modern data technologies. Terry has over 30 years of experience in data modeling and data engineering and analysis and significant experience with Machine Learning, Artificial Intelligence, and other Analytics projects. Terry holds degrees in Information Systems and Applied Mathematics and Analytics - Data Science.
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