When done right, governance is a growth engine. In this talk, Jean-Georges “jgp” Perrin will show how data contracts bring precision, trust, and accountability into your data and AI pipelines—without creating bottlenecks. Using the Open Data Contract Standard (ODCS) from the Linux Foundation’s Bitol project, you’ll see how organizations can cut downstream defects, accelerate AI model onboarding, lower compliance risk, and reduce firefighting—often in just days.

Zopa outgrew stored procedures: opaque logic, poor documentation, and inefficient pipelines. Moving to dbt Core brought modular models, tests, and version control, cutting change risk and spreading siloed knowledge. The dbt Platform then simplified onboarding, performance, and ownership, with live docs and lineage that boosted adoption and trust across teams, and supported regulatory reporting. Learn the tactics behind Zopa’s hub-and-spoke model, faster onboarding, and reusable definitions via dbt Mesh.

As AI adoption accelerates internationally, so does its environmental footprint. But what if the same technology driving innovation could also help reduce its own impact?  

From greener data infrastructure to renewable energy and smarter home tech, join us for this insightful 30-minute session with E.ON Next as they share how they are rethinking AI through an increasingly climate-conscious lens. 

Powered by: Women in Data®

Espresso AI uses two main techniques to run Snowflake workloads faster and cheaper: ML-based job scheduling and LLM-based query optimization. This talk will dive into the details behind both approaches.

As artificial intelligence reshapes the financial services landscape, modern data leaders are paving the way with empathy, innovation, and ethical clarity.  

Through personal stories, candid insights, and real-world strategies, this expert panel of Women in Data® leaders will unpack how diverse teams and inclusive leadership principles are essential to building responsible AI that reflects the customers it serves. Before leaving this session, you too will discover how passion and purpose can amplify impact in a sector too often dominated by numbers.  

Please note, this session will not be recorded so you must join us live to hear from this fantastic panel.

Powered by: Women in Data®

Get ready for a customer story that’s as bold as it is eye-opening. In this session, Eutelsat and DataOps.live pull back the curtain on what it really takes to deliver business-changing outcomes with a specific focus on the Use Cases addressed by Apache at the core. And these Use Cases are BIG – think about big, big numbers, and you still aren’t even close!

You’ll hear the inside story of how Eutelsat found itself with two “competing” cloud data platforms. What could have been an expensive headache turned out to be an advantage: Iceberg made it not only possible but cheaper and simpler to use both together, unlocking agility and cost savings that no single platform alone could provide.

The impact is already tangible. Telemetry pipelines are live and delivering massive value. Next up: interoperable Data Products seamlessly moving from Snowflake to Cloudera and vice versa, driving cross-platform innovation. And that’s just the start—Eutelsat is also positioning Iceberg as a future-proof standard for data sharing and export.

This is a story of scale, speed, and simplification—the kind of transformation only possible when a visionary team meets the right technology.

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.

It sounds simple: “Hey AI, refresh my Salesforce data.” But what really happens when that request travels through your stack?

Using Airbyte’s architecture as a model, this talk explores the complexity behind natural language data triggers - from spinning up connectors and handling credentials, to enforcing access controls and orchestrating safe, purpose-driven movement. We’ll introduce a unified framework for thinking about all types of data movement, from bulk ingestion to fine-grained activation - a model we’ve developed to bring clarity to a space crowded with overlapping terms and toolchains.

We’ll also explore how this foundation—and any modern data movement platform—must evolve for an AI-native world, where speed, locality, and security are non-negotiable. That includes new risks: leaking credentials into LLMs, or triggering unintended downstream effects from a single prompt.

We’ll close with a live demo: spinning up a local data plane and moving data via Airbyte—simply by chatting with a bot.

According to MIT, 95% of organisations are seeing no return from their GenAI investments. Why? Because value doesn’t come from models alone. It comes from trust, governance, and people. Learn how organisations are breaking through the hype using Microsoft Fabric to unify data, Purview to govern it, and Copilot to empower every user. With a real-world customer story and a clear blueprint for action, this session will help you join the 5% who are turning AI ambition into impact.

The age of autonomous agents is here, and it’s moving fast. Gartner predicts that 70% of organizations will deploy AI agents this year to automate complex business processes. But as technology vendors promise exponential productivity, data leaders face a new reality: when every team member can command thousands of digital workers, who’s really in control?

Join Dael and Robin for a candid, entertaining fireside chat as they tackle the tough questions every CDO, CTO, and CIO should be asking. How do you keep oversight when agents are making split-second decisions at scale? What new risks (ethical, operational, and reputational) emerge when AI agents go rogue? And how do you build a data strategy that balances innovation with accountability?

Using real-world stories, surprising data points, and a dash of humour, this session will help you rethink how you buy, build, and govern technology in the age of agentic business. Whether you’re already deploying agents or just starting to explore, you’ll leave with practical insights to avoid the pitfalls, and harness the promise of this next frontier.

We’re excited to be back at Big Data LDN this year—huge thanks to the organisers for hosting Databricks London once more!

Join us for an evening of insights, networking, and community with the Databricks Team and Advancing Analytics!

🎤 Agenda:

6:00 PM – 6:10 PM | Kickoff & Warm Welcome

Grab a drink, say hi, and get the lowdown on what’s coming up. We’ll set the scene for an evening of learning and laughs.

6:10 PM – 6:50 PM | The Metadata Marathon: How three projects are racing forward – Holly Smith (Staff Developer Advocate, Databricks)

With the enormous amount of discussion about open storage formats between nerds and even not-nerds, it can be hard to keep track of who’s doing what and how this actually makes any impact on day to day data projects.

Holly will take a closer look at the three big projects in this space; Delta, Hudi and Iceberg. They’re all trying to solve for similar data problems and have tackled the various challenges in different ways. Her talk will start with the very basics of how we got here, what the history is before diving deep into the underlying tech, their roadmaps, and their impacts on the data landscape as a whole.

6:50 PM – 7:10 PM | What’s New in Databricks & Databricks AI – Simon Whiteley & Gavi Regunath

Hot off the press! Simon and Gavi will walk you through the latest and greatest from Databricks, including shiny new AI features and platform updates you’ll want to try ASAP.

7:10 PM onwards | Q&A Panel + Networking

Your chance to ask the experts anything—then stick around for drinks, snacks, and some good old-fashioned data geekery.

The Data Engineer Things (DET) London Meetup focuses on hosting in-person professional networking events for the data engineering community. Join our meetup for talks from industry experts and connect with like-minded data professionals! All experience levels are welcome.

Join us for an unmissable evening of insight, discussion, and lively debate at The High Performance Data and AI Debate, hosted by Chris Tabb — a unique Big Data London special running from 6:00–8:00 PM. This fast-paced, interactive event brings together some of the brightest minds in data and AI to tackle the most pressing questions shaping the future of teams, architecture, and products in an AI-first world.

The evening kicks off at 6:00 PM with a welcome and free drinks. Then, across three rapid-fire 20-minute debates, our expert panels will explore:

• AI & Data – Teams (Chair: Eevamaija Virtanen)

Mehdi Ouazza, Paul Rankin, Jesse Anderson, Hugo Lu

• AI & Data – Architecture (Chair: Adi Polak)

Chris Freestone, David Richardson, Nick White, Karl Ivo Sokolov

• AI & Data – Products (Chair: Jai Parmar)

Kelsey Hammock, Jean-Georges (jgp) Perrin, Taylor McGrath, Jon Cooke

Refuel with free pizza at 6:50 PM, then stay for the Town Hall Debate, where all speakers return to the stage for an open-floor Q&A — your chance to challenge their ideas, share perspectives, and shape the conversation.

Expect fresh perspectives, healthy disagreement, and practical takeaways you can bring back to your organisation. Whether you’re leading a data team, designing cutting-edge architectures, or building AI-powered products, this is your space to engage with the people shaping what’s next.

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.

As AI adoption accelerates across industries, many organisations are realising that building a model is only the beginning. Real-world deployment of AI demands robust infrastructure, clean and connected data, and secure, scalable MLOps pipelines. In this panel, experts from across the AI ecosystem share lessons from the frontlines of operationalising AI at scale.

We’ll dig into the tough questions:

• What are the biggest blockers to AI adoption in large enterprises — and how can we overcome them?

• Why does bad data still derail even the most advanced models, and how can we fix the data quality gap?

• Where does synthetic data fit into real-world AI pipelines — and how do we define “real” data?

• Is Agentic AI the next evolution, or just noise — and how should MLOps prepare?

• What does a modern, secure AI stack look like when using external partners and APIs?

Expect sharp perspectives on data integration, model lifecycle management, and the cyber-physical infrastructure needed to make AI more than just a POC.

Everyone’s got a data strategy these days—but what happens after it’s written? In this candid and practical session, we’ll explore why a shiny data strategy document is just the beginning—and what it really takes to turn strategy into sustainable success.

Marion Shaw will draw on real-world experience to unpack the critical ingredients often overlooked once the strategy is signed off. From securing ongoing budget and maintaining executive buy-in, to building the right culture and keeping your data sponsors engaged, this talk will tackle the messy middle between vision and value.

You’ll leave with fresh insights on how to move from “strategy on paper” to long-term impact—along with practical tips on navigating common pitfalls, gaining traction across the business, and building momentum that lasts. If you’re serious about making your data strategy stick, this is the session for you.

Data and marketing are often treated as separate functions, but the real opportunity lies in bringing them together. In this fireside chat, Ed (Data Solutions Manager at DinMo) interviews Andrew (Head of Marketing at Brand Alley), who brings a rare dual perspective: before leading marketing, he founded and scaled a data tool for dynamic audience segmentation.

They’ll explore why data and marketing are natural teammates and how aligning the two can unlock powerful business outcomes. From enabling real-time audience activation to translating data capabilities into campaigns that drive measurable growth, the discussion will highlight practical ways to bridge the gap between teams.

Attendees will discover how to maximise the ROI of their data warehouse by embedding it into marketing workflows, ensuring data initiatives deliver clear returns through hyper-personalised customer journeys. They will walk away with actionable insights on how to make data indispensable to marketing, prove its commercial value, and create experiences that drive long-term growth.

In this, the 10th year of Big Data LDN, in its flagship Great Dat Debate keynote panel, conference chair and leading industry analyst Mike Ferguson welcomes executives from leading software vendors to discuss key topics in data management and analytics. Panellists will debate the challenges and success factors in building an agentic enterprise, the importance of unified data and AI governance, the implications of key industry trends in data management, how best to deal with real-world customer challenges, how to build a modern data and analytics (D&A) architecture, and issues on-the-horizon that companies should be planning for today.

Attendees will learn best practices for data and analytics implementation in a modern data and AI -driven enterprise from seasoned executives and an experienced industry analyst in a packed, unscripted, candid discussion.

Data leaders today face a familiar challenge: complex pipelines, duplicated systems, and spiraling infrastructure costs. Standardizing around Kafka for real-time and Iceberg for large-scale analytics has gone some way towards addressing this but still requires separate stacks, leaving teams to stitch them together at high expense and risk.

This talk will explore how Kafka and Iceberg together form a new foundation for data infrastructure. One that unifies streaming and analytics into a single, cost-efficient layer. By standardizing on these open technologies, organizations can reduce data duplication, simplify governance, and unlock both instant insights and long-term value from the same platform.

You will come away with a clear understanding of why this convergence is reshaping the industry, how it lowers operational risk, and advantages it offers for building durable, future-proof data capabilities.

The rapid evolution of AI, fueled by powerful Large Language Models (LLMs) and autonomous agents, is reshaping how we build, deploy, and manage AI systems. This presentation explores the critical intersection of MLOps and AI architecture, highlighting the paradigm shifts required to integrate LLMs and agents into production. We will address key architectural challenges, including scalability, observability, and security, while examining emerging MLOps practices such as robust data pipelines, model monitoring, and continuous optimization. Attendees will gain practical insights and actionable strategies to navigate the complexities of modern AI deployments, unlocking the full potential of LLMs and agents while ensuring operational excellence.

As AI evolves with powerful Large Language Models (LLMs) and autonomous agents, deploying and managing these systems requires new approaches. This presentation explores the crucial intersection of MLOps and AI architecture, highlighting the shift toward scalable, observable, and secure AI deployments. We’ll examine key architectural considerations for integrating LLMs and agents into production, alongside evolving MLOps practices such as robust data pipelines, model monitoring, and continuous optimization.

As AI agents become embedded in everyday workflows — from healthcare diagnostics to financial services chatbots — the line between human and machine continues to blur. This panel brings together industry leaders to tackle the tough questions:

• How do we trust AI agents in high-risk environments?

• What are the new rules of ownership and accountability when autonomous systems act on data?

• Is AI replacing or enhancing the human workforce — and how do we keep the balance right?

We'll unpack how AI agents are evolving across sectors, debate whether the current LLM paradigm is enough, and explore the new guardrails needed to futureproof agentic AI — without losing control.

Forecasting is no longer just about historical trends and spreadsheets. AI is redefining how organisations anticipate demand, manage risk and make faster, smarter decisions.

In this expert-led panel of Women in Data® senior leaders from esure, Domestic & General and Databricks, moderated by a leading voice from NTT DATA, we will explore how AI-enabled forecasting is transforming planning across industries. They will take a candid look at the current landscape, how to realign goals and priorities and how to forge a business that is dynamic, data-rich and future-ready.

Powered by: Women in Data®

As organizations increasingly adopt data lake architectures, analytics databases face significant integration challenges beyond simple data ingestion. This talk explores the complex technical hurdles encountered when building robust connections between analytics engines and modern data lake formats.

We'll examine critical implementation challenges, including the absence of native library support for formats like Delta Lake, which necessitates expansion into new programming languages such as Rust to achieve optimal performance. The session explores the complexities of managing stateful systems, addressing caching inconsistencies, and reconciling state across distributed environments.

A key focus will be on integrating with external catalogs while maintaining data consistency and performance - a challenge that requires careful architectural decisions around metadata management and query optimization. We'll explore how these technical constraints impact system design and the trade-offs involved in different implementation approaches.

Attendees will gain a practical understanding of the engineering complexity behind seamless data lake integration and actionable approaches to common implementation obstacles.

Teams in our organisations have both data and business requirements… all we have to do is train people how to use Power BI Desktop/Power Query and they can rapidly author their own MIBI reporting. By upskilling your existing staff your organisation will gain ownership of the outputs and reduce the need for contractors.

In this interactive session we will structure a 2-day Power BI training plan outline, giving all attendees an effective framework to use to deliver to their colleagues.

Behind every AI success story is a quiet set of foundations—governance, trust, and purpose-driven decisions—that most teams overlook until it’s too late. This talk reveals what the smartest companies quietly get right—and what everyone else learns the hard way. It also explores the complex, unsolved challenges on the horizon—the ones we haven’t fully mapped, but can’t afford to ignore. 

In AI, speed without the proper foundations isn’t a strategy—it’s a liability.