Institutions are drowning in complex, fragmented data ecosystems, slowing down AI adoption, increasing compliance risks, and making data governance a burden.

Without clear data lineage automation, organizations struggle with data trust, explainability, and operational inefficiencies. In this session, Adam Segal, Senior Solutions Engineer of Cloudera Octopai Data Lineage, will reveal how automated lineage and metadata intelligence can:

•  Unravel the data mess by mapping end-to-end lineage across hybrid environments
•  Ensure AI readiness with traceable, high-quality metadata flows
•  Simplify compliance with real-time visibility into data movement and ownership
•  Empower teams by making data accessible without IT bottlenecks 

Discover how leading organizations turn automated data lineage into a competitive advantage, ensuring data clarity, compliance, and increased adoption of AI-driven innovation.

Data leaders know the frustration: talented engineers spending too much time maintaining pipelines instead of driving impact. This session shows how Coalesce combines automation, standardized building blocks, and AI to free teams from repetitive work. Governance is no longer an afterthought and every data persona is empowered to deliver trusted insights at scale.

Over the last four years, ASDA has been through an incredible period of transformation. From data strategy, governance, platforms, culture, skills, and everything in between Alex Meakin (Senior Director of Data Delivery & Strategy) and his team have embraced it all and turned initials aspirations into real measurable impact. 

Brought to you by Women in Data®, Alex will be joined by moderator Robin Sutara and key partners from PwC and Databricks as he shares his honest reflections, key milestones, and practical lessons on building data maturity, driving adoption, and sustaining momentum.  

Whether you're navigating the complexities of your own transformation, still building on those early wins, or reigniting interest, this session offers practical insights, candid lessons, and fresh perspective from those who have been through it, end to end. 

Powered by: Women in Data®

Data observability helps to detect and diagnose unknown unknowns in data quality and pipeline performance—but it doesn't fix them. Learn how Bigeye is leveraging AI to enable data teams to resolve data quality and pipeline issues, and even prevent them occurring in the first place.

Artificial Intelligence (AI) is reshaping the way businesses operate, but its success hinges on more than just deploying advanced software—it requires a comprehensive strategy that makes your data AI ready, governs your models effectively, and fosters organizational transformation. ​

In this session, Precisely will be joined by elia group who will share their real-world AI journey, including their goals, challenges, and the actionable steps they are taking to overcome them. ​

Key insights include:​

- Identify the pillars of AI-ready data, ensuring accuracy, completeness, and trustworthiness.​

- Learn about the differentiating considerations for monitoring and managing the governance of AI models that align with EU AI Act.​

- Hear proven, repeatable methodologies that integrate both innovative software and change management strategies to drive success across diverse teams and foster a culture of continuous improvement.​

Building an adaptive data platform requires a complete organisational view of business capabilities to drive alignment and collaboration. In this session we discuss how to think about defining your data platform and then building based on value and organisational need.

Trusted data is the foundation for success of many business ambitions today. Organizations aspire to make data-driven decisions, but often leaders fall back on gut instincts due to fragmented data experiences. This session explores how a user-centric approach that integrates data, metadata, quality metrics, and lineage can build the necessary foundation of trust for truly data-driven decision making. Frances will share practical insights on creating holistic data experiences that empower everyone in the organization to trust their data and make confident, fact-based decisions.

In the fast-paced world of data, standing still means getting lapped. Just like in a racing game, every challenge you conquer every feature you optimise propels you to the next level. But the real goal isn’t just winning a single race; it’s winning the season.

Join Chris Tabb as he navigates the data platform circuit, showing how incremental upgrades—your turbo boosts, fresh tires, and bigger nitro fuel success.

If you wait to build the “perfect” platform before delivering, you’ve already lost. Winning teams iterate rapidly, learning from every lap to fine-tune their approach. The key? Deliver the right features at the right time—giving you the edge for the next race and the insights to dominate the season.

The teams that optimise cost-efficiency, agility, will find themselves on the podium at the end of the season.

Are you ready to accelerate your data platform maturity, and outmanoeuvre the competition?

Is there a silver bullet, panacea, one-size-fits-all, quick-fix, band-aid, easy button, magic wand solution to all your data problems?

The answer is: YES, of course, YES!

In an enterprise world where legacy systems loom large and every action creates more data, the stakes have never been higher. Amid the rising chaos, who will champion real business value over hype? 

Enter the CDO (Chief Dog Officer) and a band of unlikely allies, including the IT Bee and the CAT-sultant. Together, they navigate a landscape filled with buzzwords, battle the forces of Agentic AI, and work to transform fragmented information into tangible, actionable business outcomes.

These surprisingly relatable characters capture the personalities, tensions, and interactions found in real-world data organizations.

This session continues the Data Puppets’ tradition of analog storytelling about digital opportunities. Through video segments, behind-the-scenes glimpses, surprise guests, and live puppet performances, we will explore the exhilarating and hilarious challenges of enterprise data.

Expect laughs, insights, and inspiration to rethink your own organization's data story.

Development teams often embrace Agile ways of working, yet the systems we build can still struggle to adapt when business needs shift. In this talk, we’ll share the journey of how a cross-functional data science team at the LEGO Group evolved its machine learning architecture to handle real-world complexity and change.

We’ll highlight how new modelling strategies, advanced feature engineering, and modern MLOps pipelines were designed not only for performance, but for flexibility. You’ll gain insight into how we architected a resilient ML system that supports changing requirements, scales with ease, and enables faster iteration. Expect actionable ideas on how to future-proof your own ML solutions and ensure they remain relevant in dynamic business contexts.

Powered by: Women in Data®

DuckDB is well-loved by SQL-ophiles to handle their small data workloads. How do you make it scale? What happens when you feed it Big Data? What is this DuckLake thing I've been hearing about? This talk will help answer these questions from real-world experience running a DuckDB service in the cloud.

Ophthalmology generates vast amounts of imaging and clinical data. Yet fragmentation of this data slows both care and research. In this session, Matt Barnfield, Lead Data Engineer at Softwire, will share how we tackled these challenges in two partnerships: Moorfields Eye Hospital (UK) and Retina Consultants of America (US).

We’ll compare the parallel difficulties we encountered and the shared patterns we used to overcome them, focusing on the new, powerful tools available for trusted researchers – from clinical trial recruitments to retrospective studies.

We’ll dive into how we built cloud data platforms that ingest tens of millions of images from disparate silos and harmonise them with health records, transforming dataset curation from a manual process that took months into an automated pipeline that takes minutes. Through these case studies, we’ll show how modern data architecture can facilitate cutting-edge research and ultimately improve lives.

AI is changing every aspect of how we do our work and analytics engineering is no different. However, using AI to achieve 10x productivity improvements requires a totally new approach to how we do analytics. In this session, we will demystify how to use context engineering, and prompting techniques based on practical experience we've had at rolling our Paradime to some of the most innovative and AI-forward startups, scale-ups and enterprises.

This session features Joe, Matillion's Principal Solution Architect, in conversation with Alex R from EDF, a Lighthouse customer. EDF has already experienced the business value of Maia, with a 75% reduction in data science product delivery time and streamlining hundreds of jobs into a unified system. The discussion will highlight how Maia delivers

unprecedented productivity gains by helping customers move from legacy systems to an AI-driven data future, addressing tech consolidation and eliminating data friction. The Lighthouse program grants participants direct access to Matillion's product and engineering teams, fostering joint development and shared roadmaps, and aims to produce public-facing case studies

Self-service has always been a strong idea, but most teams never see it work the way it should. If your users can’t find answers or take action without coming back to you, it’s not self-service, it’s just a slower help desk.

The real breakdown comes from platforms that don’t match how people actually work. Self-service succeeds when it aligns with how questions form, how ideas are tested, and how decisions move from discussion to action. Without that human layer, the tools slip into the same request-and-wait cycle they were meant to replace.

From this session, you’ll get a clear view of where most programs go wrong and how to turn self-service back into what it was meant to be, something people actually use.

This session offers a strategic vision for marketing by 2027, helping businesses prepare effective strategies for 2026. It highlights key technological shifts marketers must understand to stay competitive.

Seven major trends are covered: social platforms evolving into entertainment hubs; browsers transforming into AI concierges; AI dominating the middle funnel, requiring brands to own both ends; B2C marketing adopting B2B tactics to appeal to humans and AI; blockchain resurging for luxury verification; the rise of 'Voice-to-Vision' interfaces; and gaming becoming central to AI-driven emotional connections.

To address these shifts, proposed strategies include: shifting social content toward entertainment and using AI for creation; optimizing for AI discoverability through Agent Experience Optimization (AEO); launching brand campaigns designed for AI recognition; targeting both human and AI audiences; leveraging blockchain for exclusive offers; preparing for voice-input/image-output user journeys; and treating gaming as a core marketing channel.

Attendees will gain actionable insights to adapt their strategies, optimize for AI-first interactions, and leverage emerging technologies to thrive in the evolving marketing landscape.

In this joint session, GoodData and Purple will share a field guide to turning analytics into revenue. 

Together, we’ll show you how governed, context-rich intelligence becomes paid products that customers adopt. Using Purple’s guest Wi-Fi data product as an example, we’ll unpack what’s sold, how it’s priced, and how GoodData powers it in a step-by-step runbook you can use today. 

We’ll close with what’s next: operationalizing and monetizing AI Assistants and Agents so you can charge for outcomes, not charts.

Learn how Salesforce's Data Cloud enables you to deliver great, omnichannel experiences while knowing your customer data is safe and secure.

Paradime is the pioneer in building the 'Cursor for Data' - a platform for the AI-enabled analytics engineer to achieve 10x productivity. In this lighting talk, we will showcase how Paradime and DinoAI is changing the way analytics engineering is done.

Everyone talks about AI, but few are truly winning with it. In today’s fast-paced analytics landscape, dashboards and chatbot features aren’t enough. Winning in the age of AI takes more: a unified, governed platform that brings data, AI, and people together to drive real decisions at scale.

In this session, discover how Pyramid Analytics helps organizations cut through silos, hype, and complexity to deliver smarter, faster, and more trusted decisions across the enterprise.

AI agents are the next essential enterprise capability, but they bring new complexities in control, safety, and scale. In this interactive session, see how you can design, deploy, and govern agents alongside your existing analytics and models.

The path to AI enablement runs through governance. High-quality data, model transparency, and ethical oversight aren’t barriers — they are accelerators. In this talk, we’ll connect the dots between Data Governance and AI Governance, show how unified governance, helps embed new requirements to existing processes, while fostering innovation. We will discuss actionable steps to build AI-ready organisations that innovate with proper guardrails.

Analytics engineers are at a crossroads. Back in 2018, dbt paved the way for for this new kind of data professional, people who had technical ability and could understand business context. But here's the thing: AI is automating traditional tasks like pipeline building and dashboard creation. So then what happens to analytics engineers? They don't disappear - they evolve.

The same skills that made analytics engineers valuable also make them perfect for a new role I'm calling 'Analytics Intelligence Engineers.' Instead of writing SQL, they're writing the context that makes AI actually useful for business users.

In this talk, I'll show you what this evolution looks like day-to-day. We'll explore building semantic layers, crafting AI context, and measuring AI performance - all through real examples using Lightdash. You'll see how the work shifts from data plumbing to data intelligence, and walk away with practical tips for making AI tools more effective in your organization. Whether you're an analytics engineer wondering about your future or a leader planning your data strategy, this session will help you understand where the field is heading and how to get there.

This session will explore Merlin Entertainments’ data transformation journey in partnership with Telefónica Tech. Starting from a position of minimal governance and limited internal capability, Merlin Entertainments has built a federated data strategy, implemented agile data product teams, and delivered impactful use cases such as the Genie AI. This talk will highlight how Merlin Entertainments developed a partner-agnostic delivery model to embed expertise and drive business value. Attendees will gain practical insights into structuring data teams, overcoming transformation hurdles, and leveraging partnerships to innovate at scale.

What does it mean to bring data to life? Does data take on a “LIFE” of its own, or must it be nurtured along the way? The challenge: turning raw data into valuable insights that drive action, innovation, and transformation. Although it has been said that exabytes of new information are generated daily, how much of it is meaningful? Does volume necessarily translate into value? What vision can we bring to bridge this gap? We must go beyond the surface, push the boundaries of what’s possible, and actively breathe LIFE into data to unlock its true potential.

But data’s value isn’t in the numbers alone; it's in the business decisions they inspire. In this session, we’ll explore four L.I.F.E. pillars of relevant data that will give your data meaning and impact. Blending left-brain logic with right-brain creativity, we’ll unlock powerful insights, drawing inspiration from a stunning example of data visualization ingenuity from the 1850s. This goes beyond answering questions you DO know to include exploring questions you DON'T know, turning obstacles into opportunities, and bringing data to life in a way that transforms your strategy. Are you ready to tap into the full potential of your data and drive real change in your organization? Your journey starts here.