CDAO West Coast 2025
Presentations
Day 1
Three out of four companies are betting big on AI – but most are digging on shifting ground. In this $100 billion gold rush, none of these investments will pay off without data quality and strong governance – and that remains a challenge for many organizations. Not every enterprise has a solid data governance practice and maturity models vary widely. As a result, investments in innovation initiatives are at risk of failure. What are the most important data management issues to prioritize? See how your organization measures up and get ahead of the curve with Actian.
John Weisensee
Senior Director, Solutions Engineering - Actian
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What does it take to build AI strategies that scale across not just teams—but entire industries? In this session, Rama Kattunga shares insights from her cross-sector leadership to explore how organizations can develop AI architectures that are flexible, reusable, and future-ready.
- Designing AI frameworks that transcend organizational boundaries and adapt to diverse industry demands
- Building modular data and AI infrastructure that supports rapid experimentation and innovation
- Applying AI lessons learned in one vertical to solve challenges in another
Rama Kattunga
Chief Data & Analytics Officer - ModaMate
TRACK A: Finance & Insurance Track
In today's fast-paced financial landscape, reliable data is the backbone of informed decision-making, and Artificial Intelligence (AI) is revolutionizing the way financial institutions approach risk management. As financial institutions navigate vast amounts of complex data, ensuring its accuracy and integrity is crucial for strategic initiatives, risk management, and regulatory compliance.
Join Curtis O'Dell, Global Business Director for Data Integrity, as he delves into the critical relationship between data integrity and the success of AI and ML initiatives. This session will explore:
The importance of data integrity and its impact on AI/ML initiatives
Building a resilient and trustworthy data testing system for AI success
Real-world challenges and success stories from enterprises that have achieved AI-driven results with high-quality data
Strategies for leading enterprises to confidently leverage data-driven risk management for AI-powered risk mitigation, like fraud detection
How maintaining data integrity for the regulated enterprises is crucial in providing an auditable, compliant, and a rigorous approach to managing data, conversions, and mergers.
- Revolutionizing Customer Insights: Learn how CoastHills Credit Union leveraged SurveyMonkey and Power BI to deliver next-day analytics, transforming raw customer feedback into actionable strategies that drive organizational success.
Accelerating Decision-Making: Discover how dynamic Power BI dashboards empowered leadership teams with real-time visibility into key metrics, enabling faster, data-driven decisions. - Streamlining Operations: Discover how CoastHills optimized customer feedback workflows, enhanced efficiency, and aligned those workflows with strategic business goals.
- Bridging the Business-Analytics Gap: Learn how to foster collaboration between business leaders and front-line teams to deliver world-class customer service by combining innovative solutions with practical, measurable results.
- Explore how modern data architecture principles are transforming how enterprises scale analytics and AI. Jay Sen shares practical insights into building decentralized, API-first data ecosystems that enable agility, governance, and real-time intelligence.
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- Embedding AI into strategic and operational decision-making across the enterprise
- Scaling automation to enhance agility, efficiency, and cross-functional impact
- Designing AI-native organizations built for continuous learning and innovation
- Shaping a data-driven culture that supports real-time, intelligent execution
TRACK B: Retail & Healthcare Track
- Designing for Agentic Flow in Human-Centered Healthcare AI: Explore how reasoning algorithms help AI agents navigate complex clinical workflows while fostering collaboration and trust with healthcare professionals.
- Ethics in Agentic Healthcare Systems: Learn how to embed ethical principles into AI behavior to ensure responsible, transparent, and safe decision-making in patient care.
- Advanced Reasoning Techniques for Clinical Adoption: Discover approaches like abduction to help AI make sense of incomplete clinical data—driving more accurate support and boosting confidence among clinicians.
- Psychology-Driven UX for Trust and Engagement: Explore UX strategies rooted in psychology that give AI human-like qualities to increase clinician trust, reduce cognitive load, and support adoption.
- Driving Real-World Impact in Healthcare Transformation: Examine how agentic AI is already transforming care delivery—streamlining diagnostics, optimizing workflows, and improving patient outcomes across healthcare systems.
Vice President of Design - HCA HEALTHCARE
Explore how AI and large-scale experimentation are transforming modern retail marketing. This session will dive into how data-driven testing and optimization can enhance customer targeting, improve campaign performance, and unlock new opportunities for growth. Gain practical insights into building a culture of experimentation that delivers measurable business impact.
- Large scale ML-driven Recommender system to drive global B2C streaming service subscribers’ personalized experiences and retention
- AI-powered recommendations and next best actions for B2B e-commerce platform and sales consultants to improve customer engagement and sales revenue
- Gen AI innovation to drive B2C and B2B personalization and future outlook
Duan Peng
SVP, Enterprise Head of AI, ML, and Data Science - Southern Glazers Wine & Spirits
- Explore how AI and advanced analytics are being applied to streamline eCommerce and retail operations, from inventory management to dynamic pricing.
- Learn how to integrate siloed data sources to create a unified analytics layer that supports smarter, real-time decision-making across business units.
- Understand the role of predictive models and intelligent automation in driving measurable improvements in speed, cost-efficiency, and customer experience.
- Gain insights into aligning analytics capabilities with operational strategy—ensuring cross-functional teams can act on insights at scale.
Gaurang (Gary) Patel
Sr Director, eCommerce Analytics - Albertsons Companies