Case Study

Driving data literacy in a rapidly evolving landscape

Building a data-literate organization is more challenging than ever, with shifting technologies, diverse knowledge levels across business units, and evolving AI-driven demands. Hear from one company as they share how their organization is tackling data literacy at scale—aligning education with business needs, tailoring approaches for different personas, and adapting to constant change. Gain practical insights into what works, what doesn’t, and how to foster a culture where data fluency drives smarter decision-making.

Case Study

Accelerating data value with a modern data fabric

Yash Chandaka, The Clorox Company

Clorox is driving digital transformation by rethinking how data is structured, accessed, and delivered. Join Yash Chandaka as he details how they are accelerating data value using a modern operating model built on distributed domain architecture, data platforms and fabric as infrastructure, and using a data-as-a-product mindset. Take a behind-the-scenes look to explore their approach and its impact on business outcomes.

Workshop

Mastering metadata and data lineage for governance and trust

Effective metadata management and data lineage are critical for governance, trust, and decision-making — but making them actionable is no small task. How are leading companies ensuring visibility into data pipelines, automating metadata capture, and driving adoption? Join this conversation to explore strategies for improving data discovery, compliance, and troubleshooting through intuitive lineage tools and active metadata management.

Workshop

Designing data team operating models for business impact

A great data team isn’t just about where it sits — it’s about how it operates to drive real business value. How can data leaders structure their teams to embed data into decision-making, foster strong engagement with business partners, and ensure data is used effectively across the organization? Join this workshop to discuss the operating models, hiring strategies, and engagement practices that create deep alignment between data teams and business functions. We’ll explore how to prioritize business needs, build trust, and develop a culture where data is a true driver of success.

Case Study

Transforming data strategy while driving AI & business innovation

Chris Moss, Bose

Join Chris Moss, Head of Data and Analytics CoE at Bose, as he shares their five-year journey evolving from a distributed to a federated data strategy — balancing data defense for security and compliance with data offense to drive AI, analytics, and business value. Learn how their data team enables and leads AI efforts across the enterprise, from customer insights to demand forecasting, ensuring high-quality, well-managed data and governance to maximize impact and avoid common pitfalls.

Case Study

Building a scalable data & analytics strategy

As businesses navigate economic pressures, evolving AI capabilities, and increasing data complexity, data leaders must ensure their strategies drive real business impact. Join your fellow member as they explore how to balance governance with agility, scale analytics efficiently, and integrate AI without losing sight of core data fundamentals. Learn how to align data priorities with business needs, improve data accessibility, and future-proof your organization’s analytics approach for long-term success.

Panel

Cutting through the AI hype — what’s real and what’s not?

AI is everywhere, but not every promise is being realized. Hear from your fellow senior data leaders as they separate the hype from reality, sharing insights on where AI is truly making an impact and where the challenges lie. We’ll dive into practical AI applications, the limitations of current technology, and how to avoid the pitfalls of overhyping AI in data-driven organizations. Audience engagement is encouraged as we discuss how data leaders can approach AI strategically, with a focus on measurable outcomes and sustainable growth.

Case Study

Unlocking AI’s full potential: Strategic selection, governance, and real-world impact

Ra Inta, Chevron Phillips Chemical

How do you prioritize AI projects for maximum impact? Join Ra Inta from Chevron Phillips Chemical as he shares their strategic framework for optimizing AI investments — going beyond financial metrics to consider multi-dimensional value. Explore the critical role of data governance in AI, from managing unstructured data to streamlining model implementation. Take a look behind the scenes to learn how to keep data scientists engaged with meaningful challenges while leveraging tools for optimization and machine learning. Join this session to discover how AI drives efficiencies, cost savings, and business transformation across industries through real-world examples.

Case Study

Future-proofing data governance

Traditional data governance approaches are no longer enough to keep pace with today’s AI-driven, highly regulated, and data-hungry enterprises. Join your fellow member as they explore how leading organizations are modernizing governance — shifting from rigid controls to adaptive frameworks that balance agility with compliance. Learn how to embed governance into business processes, empower data users without compromising security, and drive real business value from governance efforts in 2025 and beyond.

Workshop

Master data management: Building a single source of truth

Inconsistent, siloed, and duplicate data can derail business operations and analytics. Master data management (MDM) is key to ensuring a single, trusted source of truth — but how are leading companies making it work at scale? Join this conversation to discuss best practices for governing core data domains, integrating MDM with modern cloud architectures, and leveraging AI-driven matching and deduplication. We’ll explore how organizations are balancing centralization with flexibility, ensuring business adoption, and using MDM to drive efficiency, compliance, and data trust across the enterprise.

Workshop

Proactively managing data quality at scale

Ensuring high-quality data isn’t just about fixing errors — it’s about building systems that prevent them before they impact decision-making. How are leading companies integrating automated data validation, proactive monitoring, and governance-driven quality controls into their workflows? Join data leaders to explore strategies for real-time issue detection, scalable data contracts, self-service data quality monitoring, and AI-assisted anomaly detection. We’ll discuss how organizations are embedding data quality at every stage of the data lifecycle — ensuring trusted insights, stronger compliance, and better business outcomes.