From Wrangling to Insight: Human-in-the-Loop AI for Analytics
Together, AWS and Posit enable organizations to scale AI for analytics on a secure, open, and governed foundation by pairing the flexibility of open-source tools with the reliability and innovation of AWS AI services.
Join TDWI Research Fellow Deanne Larson, Ph.D., along with Shun Mao, Senior Partner Solutions Architect at AWS, and James Blair, Senior Product Manager at Posit, as they discuss how human-in-the-loop assistants are reshaping analytics. You’ll see a practical demo of Positron Assistant and Databot powered by Amazon Bedrock, followed by a panel discussion on real-world adoption patterns and pitfalls to avoid.
What you’ll learn:
• How human-in-the-loop AI accelerates data prep and exploration
• How to balance automation with accountability
• Best practices for adopting AI-assisted analytics responsibly
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Featured in this webinar
Shun Mao received his Ph.D. degree in software engineering from South China Normal University, Guangzhou, China, in 2025. His research has been published in journals and conferences, including IEEE Transactions on Neural Networks and Learning Systems (TNNLS), IEEE Transactions on Computational Social Systems (TCSS), Information Processing and Management (IPM), IEEE Transactions on Learning Technologies (TLT), IEEE Transactions on Consumer Electronics (TCE), International Conference on Knowledge Science, Engineering and Management (KSEM), and Pacific Rim International Conference on Artificial Intelligence (PRICAI). His research interests include machine learning, learning analysis, and artificial intelligence in education.
James Blair is a Senior Product Manager at Posit, where he focuses on helping Posit commercial products seamlessly integrate into cloud platforms and environments. He has a background in statistics and data science and finds any excuse he can to write R code and ride his bike, although usually not at the same time.
Deanne Larson, Ph.D., is an active data science practitioner and academic. Her research has focused on enterprise data strategy, agile analytics, and data science best practices. She holds Project Management Professional (PMP), Project Management Agile Certified Practitioner (PMI-ACP), Certified Business Intelligence Professional (CBIP), and Six Sigma certifications. Deanne attended AT&T Executive Training at the Harvard Business School focusing on IT leadership, Stanford University focusing on data science, and New York University focusing on business analytics. She has presented at multiple conferences including TDWI, TDWI Europe, PMI, and other academic conferences. She is a faculty member at Purdue Global, has consulted for several Fortune 500 companies, and has authored multiple research articles on data science methodology and best practices.