Join Experian for a candid Q&A with the team behind Bunches, the gifting company that delivers happiness. In this 30-minute session, they will unpack how Bunches evolved from postcode challenges to a sophisticated, data-led strategy that powers everything from seasonal segmentation to demographic profiling. Discover how Experian’s tools have helped Bunches embed data across their organisation, enhance operational efficiency, and build trust with customers, while exploring the role AI might play in their next chapter. Expect practical insights, real-world proof points, and advice for any business looking to make data everyone’s responsibility.

Data and AI solutions promise transformational value, yet most initiatives fail to reach production or deliver results. Research shows that proof‑of‑concepts help organisations assess technical feasibility, verify market needs, understand limitations and make rational budget decisions. In AI projects specifically, PoCs allow teams to 'fail fast', identify challenges early, and minimise risks.

This talk will show how adopting a PoC‑to‑value approach can unlock benefits for both vendors and customers. It will demonstrate that tools must provide time‑to‑value quickly; nearly two‑thirds of users decide whether to keep a product during their first interaction, and users may take less than 40 seconds to decide. It will also highlight why change initiatives fail when end‑users are not engaged: 70 % of change programs fail due to employee resistance and lack of management support.

While there has been much excitement about the potential of large language models (LLMs) to automate tasks that previously required human intelligence or creativity, many early projects have failed because of LLMs’ innate willingness to lie. This presentation explores these “hallucination” issues and proposes a solution.

By combining generative AI with more traditional symbolic computation, reliability can be maintained, explainability improved, and private knowledge and data injected. This talk will show simple examples of combining language-based thinking with computational thinking to generate solutions that neither could achieve on its own.

An example application of an AI scientific research assistant will be shown that brings together the ideas presented in a most demanding real-world task, where false information is not acceptable. This is a fast-evolving space with enormous potential—and we’re just getting started.

The comfortable middle ground is disappearing. Leaders face a binary choice: commit to building AI fluency (REWIRE) or focus on providing human wisdom and values in an AI world (RETIRE). Both paths have equal value, but trying to straddle them creates dangerous strategic ambiguity.

Based on Marco's research with over 100 senior executives, this keynote confronts why 67% of leaders feel "partially engaged but not fully confident" in technology discussions—a career limbo that's becoming increasingly untenable. Through contrasting stories of executives who made clear choices in either direction, audiences discover why clarity beats capability when it comes to AI—era leadership.

Key Takeaways:

• A structured decision framework based on five critical factors

• Why both REWIRE and RETIRE paths create distinctive value

• How to eliminate the anxiety that comes from strategic ambiguity

• 90-day action plan for your chosen direction

For years, data engineering was a story of predictable pipelines: move data from point A to point B. But AI just hit the reset button on our entire field. Now, we're all staring into the void, wondering what's next. While the fundamentals haven't changed, data remains challenging in the traditional areas of data governance, data management, and data modeling, which still present challenges. Everything else is up for grabs.

This talk will cut through the noise and explore the future of data engineering in an AI-driven world. We'll examine how team structures will evolve, why agentic workflows and real-time systems are becoming non-negotiable, and how our focus must shift from building dashboards and analytics to architecting for automated action. The reset button has been pushed. It's time for us to invent the future of our industry.

Step 12 months into the future - where AI agents create data products, enforce rules, and act in real time. In that world, anyone can request a new data product with a simple form and natural language prompt: “I need to predict customers likely to drop after purchasing” - and get it instantly. Who controls the pace of production so value isn’t buried under maintenance? Are data products even relevant in this new paradigm? How are AI-built assets folded back into a trusted delivery lifecycle? This session reverse-engineers what might soon be reality, exposing the issues these capabilities could bring - and the guardrails needed to keep them in check.

Are you ready to build the next generation of data-driven applications? This session demystifies the world of Autonomous Agents, explaining what they are and why they are the future of AI. We’ll dive into Google Cloud's comprehensive platform for creating and deploying these agents, from our multimodal data handling to the seamless integration of Gemini models. You will learn the principles behind building your own custom data agents and understand why Google Cloud provides the definitive platform for this innovation. Join us to gain the knowledge and tools needed to architect and deploy intelligent, self-sufficient data solutions.

Businesses spend countless hours wrangling data: extracting information from messy PDFs, building dashboards that nobody uses, and attempting to extract insights that simply don’t exist. Surely there’s a better way?

In this session, Vishal Soni and Owen Coyle will show how AI and Alteryx can work together to completely transform how you handle data. Starting with one of the toughest challenges: extracting structured information from unstructured PDFs. Instead of complex regex, manual OCR, or hours of cleanup, you’ll see how LLMs inside Alteryx can instantly convert complex documents into clean, tabular data that’s ready for analysis.

Once this data is processed: Alteryx Auto Insights can be leveraged, which produces AI-powered analysis of your data, and jumps straight to the “why” behind the numbers. You’ll quickly see how Auto Insights surfaces the most important trends, patterns, anomalies and actionable insights. All this, while generating personalized, presentation-ready reports to drive action.

Whether you’re new to Alteryx or already an experienced user, you’ll leave this session with a clear understanding of how AI is changing analytics – turning hours of manual work into instant, actional insight – and how Alteryx is that the forefront of this change.

Ten years ago, I began advocating for **DataOps**, a framework designed to improve collaboration, efficiency, and agility in data management. The industry was still grappling with fragmented workflows, slow delivery cycles, and a disconnect between data teams and business needs. Fast forward to today, and the landscape has transformed, but have we truly embraced the future of leveraging data at scale? This session will reflect on the evolution of DataOps, examining what’s changed, what challenges persist, and where we're headed next.

**Key Takeaways:**

✅ The biggest wins and ongoing struggles in implementing DataOps over the last decade. 

✅ Practical strategies for improving automation, governance, and data quality in modern workflows. 

✅ How emerging trends like AI-driven automation and real-time analytics are reshaping the way we approach data management. 

✅ Actionable insights on how data teams can stay agile and align better with business objectives. 

**Why Attend?**

If you're a data professional, architect, or leader striving for operational excellence, this talk will equip you with the knowledge to future-proof your data strategies.

Join Tom Pryor, Principal Data Engineer, as he shares how his team has harnessed the power of Snowflake to transform their data strategy into a robust, scalable foundation for digital innovation and AI enablement. This session will explore how Snowflake has unified data across the enterprise, enabling real-time insights, powering customer-facing digital applications, and laying the groundwork for advanced AI capabilities. Tom will walk through key architectural decisions, data governance practices, and the evolution from legacy systems to a modern data platform.

AI innovation shouldn’t be gated by pipeline delays or data migrations. This session shows how federated data products deliver instant, trusted access—fueling chatbots, agents, and multi-agent workflows that solve real business problems.

We’ll walk through examples of a semantic layer built with data products that power both BI and AI. You’ll see how data products ensure more accurate AI results, simplify governance, and support experimentation with any LLM or agent framework.

Real-world use cases will include:

* A 1-day chatbot business project for answering questions with governed data

* An autonomous agent driving decisions from live sources

* A multi-agent workflow delivering dynamic, real-time insights

Leave with a practical blueprint to accelerate AI—no warehouse rewrites, no delays, just results.

Business challenges that were once sporadic are now persistent and widespread—impacting everyone across the organization, from business users and analysts to data engineers and scientists.

To keep pace, BI platforms have steadily evolved, embracing technologies that empower every user to tackle growing data complexity with confidence.

Now, with sophisticated Gen AI and Agentic AI capabilities built into these platforms, we’re stepping into a new era of analytics—one that redefines what data democratization means for modern businesses.

Join us for an exclusive session where we’ll explore how the latest innovations in Gen AI are reshaping the BI landscape and unlocking powerful, actionable insights for every user.

In this session, you’ll learn:

- What defines a truly Gen AI-powered BI platform

- How businesses can empower every user with cutting-edge Gen AI

- How Agentic AI is shaping BI

- Live demos showcasing Gen AI and Agentic AI capabilities in BI

- Discover how a Gen BI platform can drive smarter decisions, boost productivity, and deliver transformative business outcomes.

In this fireside chat, IT Analyst Yegor Yarko from JetBrains shares their team’s AI journey: starting with enterprise search to unify knowledge, then layering AI to accelerate discovery. Learn how they are streamlining access to information through AI-powered search, and creating a trusted foundation for AI. Hear first-hand how they determined whether to build vs. buy an enterprise search solution, the change management that is helping to drive adoption, and pragmatic steps you can apply to boost productivity across your organization.

AI is changing the game across industries, but one of its most powerful and urgent applications is in combating climate change. From optimizing renewable energy grids to improving carbon capture and making supply chains more sustainable, AI is playing a crucial role in driving real-world impact.

In this talk, Russell Dalgleish—entrepreneur, investor, and a leading voice in Scotland’s sustainability and innovation scene—dips into how AI-driven solutions like predictive analytics, and intelligent automation are reshaping the path to net zero. He’ll share lessons from Scotland’s thriving Greentech sector, offering practical insights on how businesses can harness AI to meet sustainability goals while staying ethical and responsible.

If you’re a business leader, policymaker, or innovator looking to turn AI into a force for good, this session is for you.

Many data teams are under pressure to organizations leverage AI, but few recognize that AI is only as powerful as the data behind it. In this session, industry veteran Adam Greco will use humor and storytelling to explore why companies often struggle to centralize customer data and how fragmented, team-owned datasets undermine AI’s potential. He will highlight how executives sometimes turn to AI as a shortcut, overlooking the fundamental need to fix core data challenges first.

Drawing on decades of experience, Adam will explain how AI inevitably magnifies the quality of your current data—accelerating either insights or errors. He will show how the urgency of AI adoption can serve as a catalyst for improving data governance, centralization, and accessibility. Once organizations establish a single source of truth, AI can be harnessed to deliver meaningful efficiencies, empower marketers with real-time access, and drive smarter decision-making across the enterprise.

Attendees will walk away with a practical understanding of why clean, centralized data is the foundation of AI success—and how to position AI as an enabler of transformation, not a distraction from data realities.

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.

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.​

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®

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

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.