Main Day 1 - Wednesday 21st January

With vast experience in large-scale enterprise data products, Sanchit Juneja offers rare insight into scaling data as a product across complex organisations. The session will cover practical lessons regarding everything from internal ML models to semantic frameworks, highlighting topics such as:

• Scaling machine learning operations to support enterprise-wide data products.
• Navigating semantic complexity to improve data discoverability and usability.
• Connecting internal models and public data assets to drive strategic value.

Sanchit Juneja

Senior Director - Big Data & ML/AI Products
Tripadvisor

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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

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Presentation – Session to be Announced

David Pires

Director, Analytics Platform and Products
Expedia Group

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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

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Session to be Announced – Sponsored by The Modern Data Company

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.

Ime Akpan

Head of Data Engineering
Vanguard

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Juan Carlos Vázquez

Director - Data Platform
Delivery Hero

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Jialiang Zhang

Director, Privacy, AI & Data Responsibility
Mastercard

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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. Through a detailed use case, 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

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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

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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

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Shrey Shivam

Sr Director, Head of Data, Analytics & AI
Fiserv

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Jialiang Zhang

Director, Privacy, AI & Data Responsibility
Mastercard

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Kate Sargent

Chief Data Officer
Financial Times

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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

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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

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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

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John Burton

Head of Data, Analytics and Insight
Stagecoach

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Nivedh R Iyer

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

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Steve Morgan

Senior Data Platform Architect
Starburst

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