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.

You’ve rolled out self-service analytics. Everyone’s answering their own questions. Job done, right? Not quite.

Together with ThoughtSpot, Huel shares what comes next when your organisation has fully embraced self-service analytics. From redefining the role of the data team, to unlocking a culture of empowerment for business users to go from reactive insights to proactive decisions, discover how Huel is going beyond dashboards and into a new era of analytics. If you’ve nailed self-service, or even if you haven't, this is your roadmap to what’s next.

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.

Join Amperity’s Principal Product Architect to learn more about innovations in the Lakehouse space and how companies are building efficient and durable architectures. This session will include a deep dive into building a composable data ecosystem centered around a lakehouse, followed by reviewing real world application of these concepts through Amperity Bridge, an exciting new technology to plug software solutions into a lakehouse.

As NiFi scales, so do the NiFi Data flow deployment headaches. CI/CD helps, but incomplete automation still leaves teams tied to the NiFi UI for adjusting parameters, updating controller services, and managing variables/parameter contexts by hand. This slows releases, increases operational risk, and strains engineering time.

This talk explores a game-changing, centralized platform, Data Flow Manager (DFM), that brings true end-to-end automation to NiFi data flow deployments. Configure, validate, and deploy Nifi data flows across dev, staging, and production environments without ever logging into the NiFi UI. Everything is handled in one place, with full integration into your existing CI/CD pipelines.

We’ll cover a few out-of-the-box features of Data Flow Manager – scheduled NiFi data flow deployments, centralized Access control management, data flow Sanity checks, Audit logging, and Monitoring NiFi-specific metrics, creating predictable, scalable, and error-free NiFi data flow deployments across environments. The goal is simple: reduce operational overhead, eliminate manual errors, and bring predictability to NiFi data pipelines at scale.

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

The world’s appetite for data is exploding—but so is its environmental cost. Every email sent, file stored, and video streamed requires energy to process, store, and transmit, leaving a growing carbon footprint that’s largely invisible to most businesses. This session lifts the lid on the hidden strain our digital lives place on the planet, exploring the link between data growth and environmental impact. The team at CompressionX will share how innovative approaches to data storage and transfer can drastically cut energy use without compromising performance, you’ll discover practical strategies any organisation can adopt to reduce its digital carbon footprint. The takeaway: sustainability isn’t just about renewable energy or greener infrastructure—it’s about rethinking the way we manage information itself.

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.

The data landscape is fickle, and once-coveted roles like 'DBA' and 'Data Scientist' have faced challenges. Now, the spotlight shines on Data Engineers, but will they suffer the same fate? This talk dives into historical trends.

In the early 2010’s, DBA/data warehouse was the sexiest job. Data Warehouse became the “No Team.”

In the mid-2010’s, data scientist was the sexiest job. Data Science became the “mistaken for” team.

Now, data engineering is the sexiest job. Data Engineering became the “confused team”. The confusion run rampant with questions about the industry: What is a data engineer? What do they do? Should we have all kinds of nuanced titles for variations? Just how technical should they be?

Together, let’s go back to history and look for ways on how data engineering can avoid the same fate as data warehousing and data science. This talk provides a thought-provoking discussion on navigating the exciting yet challenging world of data engineering. Let's avoid the pitfalls of the past and shape a future where data engineers thrive as essential drivers of innovation and success.

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.

This session will explore the evolving role of data engineers. Data engineering is currently a bottleneck due to overwhelming requests and complex knowledge work. Maia acts as a "digital data engineer" or a "virtual data team" that amplifies productivity by 100x. It enables users, from skilled engineers to citizen data analysts, to author pipelines in natural business language. The session will demonstrate Maia's ability to accelerate mundane and advanced tasks,troubleshoot and debug pipelines in real-time, and generate high-quality, auditable pipelines using Matillion's proprietary, human-readable Data Pipeline Language (DPL), which avoids "spaghetti code" common with generic LLMs.

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.

We all understand the importance of a business brand or a personal brand. But every team has a brand too - a reputation that shapes how others see you, trust you, and choose to work with you. The challenge is that most leaders don’t intentionally define it.

In this interactive VIP session, Helen Mannion will guide senior leaders through a Team Brand 360 reflection, exploring how their teams are perceived today and how they want to be known tomorrow. Drawing on lessons from personal branding and customer experience, she’ll show how the same principles - clarity, consistency, and visibility - can help teams strengthen their identity and influence.

Attendees will leave with practical tools to start shaping their team brand and fresh insight into how a structured Team 360 process, training, and coaching can accelerate adoption and embed culture change at scale.

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.

Data Stacks have traditionally been comprised of all-in-one, monolithic solutions. Powerful, but often rigid, expensive, and slow to adapt. In this session, we’ll explore how a composable architecture flips that model on its head, giving teams the flexibility to integrate best-in-class tools, scale on demand, and move faster. We’ll walk through a practical use case comparing a traditional CDP with a composable approach, highlighting the trade-offs and the tangible benefits in agility, cost, and business impact.

What happens when cutting-edge data meets disruption? In this half-hour session, leading Women in Data® voices from some of the biggest names in the insurance sector will explore how innovative data and analytics are reshaping finance for a more resilient future.  

From climate risk and regulatory shifts to customer behaviour and operational efficiency, this session will unlock how insurers are using their data to adapt and stay ahead of the curve in our rapidly changing world. 

Powered by: Women in Data®

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.

People are emotional, irrational and unpredictable – and yet they are the most important aspect of any data strategy. Tiankai introduces his framework of the 5 Cs – competence, collaboration, communication, creativity and conscience – with actionable examples to help you put the human being really at the center of your data efforts, and to turn your team members and employees into active advocates for your data strategy.

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.