Conference Day 1
8:00 am - 8:45 am
Registration & Breakfast
8:45 am - 9:00 am
Opening Chair Remarks
9:00 am - 9:30 am
Opening Panel Discussion: Embedding Data Product Thinking Across the Business to Drive Adoption and Better Decisions
Elcio Abrahao -
Platform Director - Head of Data,
Syngenta
Yang Zhou - Head of Data Engineering & Platforms, DFDS
Rohit Shankarmani - AI/ML/Data Product Lead, A.P. Maersk
Many organisations invest heavily in platforms and tools but struggle to realise value due to cultural resistance and misaligned incentives. This panel explores how enterprises manage the cultural shift required to support data products, AI adoption, and new ways of working, particularly across functions that have not traditionally engaged deeply with data.
Aligning incentives and behaviours to support product thinking
Embedding data and AI into everyday decision making
Supporting organisation wide adoption through culture and leadership
9:30 am - 10:00 am
Presentation: Designing Data Products for a World of AI Agents
Rafael Laffarga Leo -
Head of Product Data, AI & Digital Employee Experience,
Roche
Data platforms weren't built for agents that act, decide, and operate on sensitive data. Yet across many organisations, that is already the reality: data products are being consumed not just by people, but by AI systems working across domains like people and finance. At Roche, Rafael Laffarga is rethinking how data products and platforms are designed so they can support this shift. With a growing catalogue of governed data products and federated ownership in place, the focus is moving towards making these products usable, traceable, and safe for both human and agent-driven consumption, without slowing down value creation across the business. This includes tackling new questions around ownership, lifecycle, and cost, as well as understanding what agents are interacting with data, how they behave, and how their actions can be tracked and improved over time.
Designing data products and platform capabilities that support both human and agent-driven use cases
Aligning federated ownership, governance, and lifecycle practices to ensure consistent, reusable data products
Implementing observability and identity mechanisms that make AI-driven interactions traceable and accountable
10:00 am - 11:00 am
Morning Coffee Break & Speed Networking
11:00 am - 11:30 am
Presentation: Business First, Data Second: Building Data Products That Actually Deliver Value
Junhui Wang -
Head of Data Platforms & Analytics,
Huhtamaki
Many organisations invest heavily in data platforms and tools, yet still struggle to deliver meaningful business value. Too often, data initiatives are driven by technology rather than real demand, leading to low adoption, poor data quality, and missed opportunities to generate ROI.
At Huhtamaki, Junhui shares her expertise on building data products through a business-led approach, aligning closely with stakeholders to ensure every capability supports real outcomes, exploring how to create strong data foundations, improve data quality at the source, and evaluate new initiatives based on value, scalability, and long-term impact rather than hype.
Aligning data products with business priorities to ensure relevance, adoption, and measurable value
Strengthening data foundations by improving data quality at the point of creation and embedding best practices
Evaluating and scaling data product opportunities by balancing ROI, cost, and long-term sustainability
11:30 am - 12:00 pm
Session Details to be Announced!
Orsolya Salla -
Director - Head of Data Privacy,
BorgWarner
12:00 pm - 1:30 pm
Lunch
1:30 pm - 2:00 pm
Panel Discussion: What Makes Data Products Truly Scalable and Worth the Investment
Juan Carlos Vázquez -
Director, Data Platform,
Delivery Hero
For many data leaders, the challenge is no longer building data products but ensuring they deliver consistent value at scale. As definitions vary and demand grows, questions remain around ownership, reuse, and how to avoid creating more complexity instead of less.
This panel brings together senior data leaders to define what truly differentiates high-performing data products, focusing on the decisions, trade-offs, and structures that enable scale, trust, and long-term impact.
Defining the characteristics that make data products scalable, usable, and trusted across the enterprise
Aligning ownership and product thinking across data, platform, and business teams
Connecting platform, governance, and ownership decisions to measurable business value
2:00 pm - 2:30 pm
Presentation: From Data Chaos to AI that is Auditable, Explainable & Trusted at Scale
Gabor Harsanyi -
Head of Data,
Ericcson
AI is accelerating across organisations, but data foundations are not keeping up. Tools multiply, teams move independently, and ownership remains unclear, leaving gaps in metadata, quality, and accountability that quietly undermine trust. Gabor Harsanyi explores the reality inside Ericcson in navigating fragmented platforms and parallel data environments, where instead of slowing innovation with AI, the focus shifted to strengthening metadata, embedding governance into everyday workflows, and making ownership visible across teams.
Connecting fragmented data sources through practical metadata and catalogue approaches that expose context and ownership
Embedding governance, privacy, and data quality into workflows so accountability sits with the teams using the data
Shifting conversations with leadership from AI capability to AI accountability through clear, outcome-led storytelling
2:30 pm - 3:00 pm
Presentation: From Teams to Products: Redefining Ownership, Flow, and Collaboration at Just Eat Takeaway
Theo Gough -
Data & Analytics, Head of Startegy, Governance & Experimentation Enablement,
Just Eat Takeaway.Com
At Just Eat Takeaway, data products have become more than a delivery model, they are a way to redefine how teams work together. As demand for data grows, the challenge shifts from building solutions to managing ownership, flow, and accountability across engineering, analytics, and business teams. Theo Gough shares how applying product thinking to data is reshaping the operating model, introducing clearer boundaries, reducing friction, and enabling teams to move from reactive delivery to more structured, collaborative ways of working.
Defining ownership and accountability by introducing data products as bounded units with clear responsibilities and service expectations
Enabling collaboration across engineering, analytics, and business teams through shared contracts and product-led workflows
Managing demand and improving delivery flow by shifting teams from reactive execution to structured, product-driven approaches
Theo Gough
Data & Analytics, Head of Startegy, Governance & Experimentation EnablementJust Eat Takeaway.Com
3:00 pm - 3:30 pm
Afternoon Coffee Break
3:30 pm - 4:00 pm
Panel Discussion: Maintaining Trust, Security and Control as Data Products, Self Service and AI Scale
Agata Reistenbach Oleksy -
Associate Director of Data Engineering,
Brenntag
Gabor Harsanyi - Head of Data, Ericcson
Francesco Fersini - Head of Data Platform and Governance, UBS
As data products, self service access, and AI adoption expand, governance complexity increases significantly. This panel brings together data, governance, and risk leaders to discuss how governance models evolve to support scale, automation, and regulatory pressure while still enabling teams to deliver at pace.
Scaling governance across products, platforms, and AI workloads
Aligning data, risk, and compliance teams around shared objectives
Maintaining trust and control as data usage expands
4:00 pm - 4:30 pm
Presentation: Data Products as the Foundation for Federated Governance
Andreas Madsen -
Director, Head of Enterprise Data Platforms,
Lundbeck
Investing in modern data platforms to accelerate analytics and AI is now a must, but enterprises are struggling to scale governance as platforms, domains, and teams multiply. The result is often fragmented ownership, duplicated logic, inconsistent KPIs, and limited trust in data.
At Lundbeck, Andreas Madsen is leading the evolution of a federated enterprise data ecosystem built around governed data products rather than platform consolidation. Instead of forcing all workloads onto a single technology stack, Lundbeck is establishing shared governance, semantics, and discovery across SAP, Snowflake, and Microsoft Fabric through a product-centric operating model, enabling federated platforms to operate as a single governed ecosystem.
Establishing clear ownership and accountability by defining data contracts and product boundaries
Enabling shared semantics and reusable logic across domains to reduce inconsistency and duplication
Creating unified discovery and cross-platform governance through marketplace and lineage capabilities
4:30 pm - 5:00 pm
Presentation: Speed Without Sacrifice: Balancing Governance and Delivery in UBS's Data Product Platform
Francesco Fersini -
Head of Data Platform and Governance,
UBS
UBS operates across a highly complex data environment, with multiple platforms, regulatory requirements, and teams spanning over 100+ countries. Here the challenge is not access, but how quickly governed, usable data can be delivered. Francesco, Product Lead of Data and Governance Platform at UBS, shares how his team is evolving their data product and platform approach to address this. Rather than introducing more process, the focus has been on simplifying and adapting workflows, improving discoverability, and using AI to support how data products are built and consumed. This includes early work towards an agent-enabled data platform, where complexity is reduced and teams are guided through the creation and use of data products in a more structured way.
Balancing delivery speed and governance by refining processes and embedding guidance into data product development
Improving discoverability and accessibility so teams can find, understand, and use data products at scale
Using AI and agent-based support to simplify platform complexity and support more efficient data product creation
