Main Day 1 - Wednesday 21st January

As organisations intensify their investment in AI, many still face familiar challenges: fragmented architectures, governance constraints, and business teams unable to access the data they need at the pace the business demands. In this session, Adrian Estala, CDAIO at Starburst, will outline how leading enterprises are overcoming these hurdles by adopting a business-centric semantic layer built on logical, federated data products—without the disruption of large-scale migrations or centralised rebuilds. You’ll hear how data and analytics leaders are:

• Enabling true self-service for business users through governed, reusable data products
• Reducing costs and accelerating time-to-value by reusing trusted components for emerging AI initiatives.
• Supporting rapid experimentation across domains with data that aligns to real business outcomes.
• Simplifying legacy complexity to speed up both BI and AI delivery.
• Embedding scalable, policy-driven governance throughout the entire data product lifecycle.

Adrian Estala

VP, Chief Data and AI Officer
Starburst

See Bio

Self-service is often treated like the end goal. In practice, it’s just one way of working, brilliant in some moments, frustrating in others. The same dynamic plays out in data organisations. The friction starts when we expect platforms and products to behave like the other, or when the “in between” work is left vague: who owns quality, definitions, changes, and support when things don’t fit the happy path? This session looks at why the boundary naturally blurs, how to spot the predictable friction points, and how to design an operating model that allows teams to move between autonomy and guided support without blame or bureaucracy by:

• Assessing why the platform/product line is rarely clean in real life, and what tends to break when organisations pretend it is.
• Knowing how to recognise the moments when self-service should pause and a more guided support path needs to kick in.
• Designing practical ways to integrate “intentional flex”: what to standardise, what to leave to product teams, and how to make transitions feel seamless.
• Studying ownership patterns that stop work from disappearing into the cracks (data quality, experience, reliability, change management).
• Protecting trust as you scale: clear expectations, support routes, feedback loops, and decision rights.

David Pires

Director, Analytics Platform and Products
Expedia Group

See Bio

As data becomes central to every business function, empowering departments beyond the data team to understand, manage and leverage their own data is no longer optional, it's strategic. This session explores how cross-departmental data literacy reduces strain on central teams, improves governance, and unlocks new opportunities for data product development by:

• Enabling departments to identify, interpret and act on their own data assets.
• Establishing scalable training and tooling to foster data ownership across teams.
• Clarifying what data can be shared, and how, according to current and evolving data governance policies.

Saielle DaSilva

Head of Product Strategy
Sainsbury's

See Bio

The future of computing is about building intelligent devices, not just faster ones. As Lenovo transforms from the world's largest PC manufacturer into an intelligent devices company where every laptop, tablet, and workstation becomes a source of insight, they faced a challenge: How do you unify data from 180 million devices across 160 markets while enabling hundreds of data scientists to deploy AI models in weeks instead of quarters?

Traditional data platforms promised the world but delivered 18–24-month timelines, vendor lock-in, and restrictive architecture choices. Lenovo needed something fundamentally different, a true data operating system that treats data products as reusable building blocks rather than one-off pipelines and provides a unified semantic layer that gives AI models the business context they need.

In this session, learn how Lenovo went from concept to production data products in less than 8 weeks, and how these building blocks now drive measurable value across warranty prediction, customer personalization, and new revenue streams.

Girish Hoogar

Global Head of Technology
Lenovo

See Bio

Sachin Dharmapurikar

Vice President of Client Technology
The Modern Data Company

See Bio

As data demands grow, decentralising platforms offers a powerful path to agility, scalability, and innovation. This session explores the benefits and challenges of decentralised architectures, with a spotlight on a real-world case study showcasing the shift to a self-serve, cloud-agnostic model. Learn how leading enterprises are:

• Implementing decentralised data platforms to empower teams and reduce bottlenecks.
• Leveraging self-serve models to accelerate access and improve operational efficiency.
• Integrating cloud-agnostic solutions to future-proof enterprise data strategies.

Juan Carlos Vázquez

Director - Data Platform
Delivery Hero

See Bio

Jialiang Zhang

Director, Privacy, AI & Data Responsibility
Mastercard

See Bio

Jean-Georges Perrin

Senior Product Manager
Actian

See Bio

During this session led by Pablo Kotey, Head of Data Enablement at Schroders, he’ll share how his team develops data products around an offensive data strategy which delivers measurable business value. By focusing on demand, speed, and governance, they’ve created a framework that eliminates wasted space and fills critical data product gaps. Pablo will detail how his team is:

• Building data products that respond directly to business demand.

• Monitoring product fitness to ensure continued relevance and optimisation.

• Scaling development by continuously improving their data mesh, tooling, and governance structures.

Pablo K

Head of Data Enablement
Schroders

See Bio

In this fireside chat, Mark O’Brien, Director of Product at Shutterstock, will explore how enterprises can unlock new value from their data by reimagining it as a product. The discussion will cover industry-wide challenges and opportunities, including:

• Assessing where data has the strongest commercial potential.
• Building standards and enrichment approaches that scale across use cases.
• Creating frameworks that better connect data with customer workflows and demand.

Mark O'Brien

Director of Product
Shutterstock

See Bio

As data becomes one of the most valuable assets in the enterprise, and more of it becomes available, monetisation offers a compelling opportunity to drive revenue and data product innovation. This panel explores the strategic, operational, and regulatory considerations required to turn raw data into market-ready products. Learn how to fully leverage your data-assets and build a sustainable monetisation framework by:

• Establishing the right mix of people, processes, and platforms to support monetisation.
• Considering ever-evolving privacy, quality, and consistency challenges from the start.
• Creating innovative data products that meet market needs.

Michael Hejtmanek

Head of Data Consulting
Neudata

See Bio

Shrey Shivam

Sr Director, Head of Data, Analytics & AI
Fiserv

See Bio

Kate Sargent

Chief Data Officer
Financial Times

See Bio

In this presentation led by Jivesh Juneja, Head of Data Products at Nissan Motor Corporation, he’ll share how his team leverages data platforms to build targeted data products that power customer personalisation, particularly across sales and marketing. As a company that sees itself as a data delivery organisation, Nissan has developed data product portfolios that assess lifecycle value, identify user needs, and guide strategic decisions around retention and growth. This session explores how data products can help improve team structure and drive business value by:

• Enabling personalised customer engagement and revenue acceleration.
• Managing all data product lifecycles, retiring legacy assets, and identify new opportunities.
• Fostering ownership, agility, and strategic alignment across teams.

Jivesh Juneja

Head of Data Products
Nissan Motor Corporation

See Bio

Forecasting the success of data products requires more than intuition, it demands transparency, agility, and real-time insight. This session showcases a live enterprise project that harnesses predictive analytics leveraging data-based and opinion-based insights. Learn how today’s analytics can bring to the forefront what your clients truly want, before they even ask by:

• Replacing outdated forecasting models with dynamic, real-time analytics.
• Establishing client transparency to eliminate assumption-based decision-making.
• Reframing predictive analytics as a client-centric strategy rather than a technical exercise.

Claudia Villasis-Wallraff

Head of Data Driven Treasury
Deutsche Bank

See Bio

Data governance is often framed as a regulatory necessity, which it is, but its true value lies in enabling smarter, more cost-effective decisions. Through practical takeaways, this panel brings together seasoned leaders to share how reframing governance as a business enabler can unlock executive support by:

• Shifting the narrative from regulation to strategic enablement.
• Demonstrating how strong data and governance frameworks directly impact AI implementation, quality, cost, and data products.
• Aligning governance with business value and growth so it’s not an afterthought.

Sarah Phenix

Head of Data Governance
Munich Re Specialty

See Bio

John Burton

Head of Data, Analytics and Insight
Stagecoach

See Bio

Nivedh R Iyer

Head of Group Data Management, Group Data & Analytics
Danske Bank

See Bio

Steve Morgan

Senior Data Platform Architect
Starburst

See Bio