For years, data governance has been about guiding people and their interpretations. We build glossaries, descriptions and documentation to keep analysts and business users aligned. But what happens when your primary “user” isn’t human? As agentic workflows, LLMs, and AI-driven decision systems become mainstream, the way we govern data must evolve. The controls that once relied on human interpretation now need to be machine-readable, unambiguous, and able to support near-real-time reasoning. The stakes are high: a governance model designed for people may look perfectly clear to us but lead an AI straight into hallucinations, bias, or costly automation errors.

This session explores what it really means to make governance “AI-ready.” We’ll look at the shift from human-centric to agent-centric governance, practical strategies for structuring metadata so that agents can reliably understand and act on it, and what new risks emerge when AI is the primary consumer of your data catalog. We'll discuss patterns, emerging practices, and a discuss how to transition to a new governance operating model. Whether you’re a data leader, platform engineer, or AI practitioner, you’ll leave with an appreciation of governance approaches for a world where your first stakeholder might not even be human.

Governance thrived on human nuance. But when AI’s the main consumer, what does ‘understanding’ even mean now?

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.

Get fresh AI updates, expert insights on open formats, and network with the brightest minds in data - all in one evening.

Analytical Data Product success is traditionally measured with classic reliability metrics. If we were ambitious, we might track user engagement by dashboard views or self-serve activity; they are blunt, woolly indicators at best. The real goal was always to enable better decisions, but we often struggle to measure whether our data products actually help. Conversational BI changes this equation. Now we can see the exact questions users are asking, what follow-ups they need, and where the data model delights or frustrates them. This creates a richer feedback loop than ever before, but it also puts our data model front and centre, exposed directly to business users in a way that makes design quality impossible to hide.

This session will recap the foundations of good data product design, then dive into what conversational BI means for analytics teams. How do we design models that give the best foundation? How can we capture and interpret this new stream of usage feedback? What does success look like? We'll answer all of these questions and more.

Data’s not what it was. Analytics is shifting fast - so how should we rethink data product design before we’re left in the dust?

The demand for data engineering keeps growing, but data teams are bored by repetitive tasks, stumped by growing complexity and endlessly harassed by an unrelenting need for speed. What if AI could take the heavy lifting off your hands? What if we make the move away from code-generation and into config-generation — how much more could we achieve? In this session, we’ll explore how AI is revolutionizing data engineering, turning pain points into innovation. Whether you’re grappling with manual schema generation or struggling to ensure data quality, this session offers practical solutions to help you work smarter, not harder. You’ll walk away with a good idea of where AI is going to disrupt the data engineering workload, some good tips around how to accelerate your own workflows and an impending sense of doom around the future of the industry!

Two industry veterans have been debating data architecture, tearing apart trends and tinkering with tech for decades and they’re bringing the conversation live — and you’re in control. Got a burning question about lake structures or internal performance? Worried about AI taking over the world? Want straight-talking opinions on the latest hype? Need real-world advice from the people who the experts get advice from? Want to get the juicy behind-the-scenes gossip about any announcements and shockwaves from the Keynotes? This is your chance to have your questions answered! Submit your questions ahead of time or bring them on the day — no topic is off-limits (though there's always a risk of side quests into coffee, sci-fi, or the quirks of English weather). Come for the insights, stay for the chaos.

Picture the scene — you're exploring a deep, dark cave looking for insights to unearth when, in a burst of smoke, Genie appears and offers you not three but unlimited data wishes. This isn't a folk tale, it's the growing wave of Generative BI that is going to be a part of analytics platforms. Databricks Genie is a tool powered by a SQL-writing LLM that redefines how we interact with data. We'll look at the basics of creating a new Genie room, scoping its data tables and asking questions. We'll help it out with some complex pre-defined questions and ensure it has the best chance of success. We'll give the tool a personality, set some behavioural guidelines and prepare some hidden easter eggs for our users to discover. Generative BI is going to be a fundamental part of the analytics toolset used across businesses. If you're using Databricks, you should be aware of Genie, if you're not, you should be planning your Generative BI Roadmap, and this session will answer your wishes.

Details to be confirmed soon

PANEL: In an era where data drives decision-making and innovation, data engineering stands at the forefront of technological advancement.

In an era where data drives decision-making and innovation, data engineering stands at the forefront of technological advancement. 

This panel brings together leading experts; Chad Sanderson, Joe Reiss, Sarah Levy and Pushkar Garg to explore the critical challenges and opportunities shaping the field today.

Accurate, reliable, and timely data is critical for CPG companies to stay ahead in highly competitive retailer relationships, and for a company like the Hershey Company, the commercial relationship with Walmart is one of the most important. The team at Hershey found themselves with a looming deadline for their legacy analytics services and targeted a migration to the brand new Walmart Luminate API. Working in partnership with Advancing Analytics, the Hershey Company leveraged a metadata-driven Lakehouse Architecture to rapidly onboard the new Luminate API, helping the category management teams to overhaul how they measure, predict, and plan their business operations.

In this session, we will discuss the impact Luminate has had on Hershey's business covering key areas such as sales, supply chain, and retail field execution, and the technical building blocks that can be used to rapidly provision business users with the data they need, when they need it. We will discuss how key technologies enable this rapid approach, with Databricks Autoloader ingesting and shaping our data, Delta Streaming processing the data through the lakehouse and Databricks SQL providing a responsive serving layer. The session will include commentary as well as cover the technical journey.

Talk by: Simon Whiteley and Jordan Donmoyer

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

Simon and Denny have been discussing and debating all things Delta, Lakehouse and Apache Spark™ on their regular webshow. Whether you want advice on lake structures, want to hear their opinions on the latest trends and hype in the data world, or you simply have a tech implementation question to throw at two seasoned experts, these two will have something to say on the matter. In their previous shows, Simon and Denny focused on building out a sample lakehouse architecture, refactoring and tinkering as new features came out, but now we're throwing the doors open for any and every question you might have.

So if you've had a persistent question and think these two can help, this is the session for you. There will be a question submission form shared prior to the event, so the team will be prepped with a whole bunch of topics to talk through. Simon and Denny want to hear your questions, which they can field drawing from a wealth of industry experience, wide ranging community engagement and their differing perspectives as external consultant and internal Databricks respectively. There's also a chance they'll get distracted and go way off track talking about coffee, sci-fi, nerdery or the English weather. It happens.

Talk by: Simon Whiteley and Denny Lee

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

Hear from two guests. First, Simon Whiteley (co-owner, Advancing Analytics) on his reaction to industry announcements, where he sees the industry heading, and an introduction to his community at Advancing Analytics. Second guest, Matteo Quattrocchi (Director - Policy, EMEA at BSA | The Software Alliance) on the current state of AI policies - by international governments, global committees, and individual companies.. Hosted by Ari Kaplan (Head of Evangelism, Databricks) and Pearl Ubaru (Sr Technical Marketing Engineer, Databricks)

Simon and Denny Build A Thing is a live webshow, where Simon Whiteley (Advancing Analytics) and Denny Lee (Databricks) are building out a TV Ratings Analytics tool, working through the various challenges of building out a Data Lakehouse using Databricks. In this session, they'll be talking through their Lakehouse Platform, revisiting various pieces of functionality, and answering your questions, Live!

This is your chance to ask questions around structuring a lake for enterprise data analytics, the various ways we can use Delta Live Tables to simplify ETL or how to get started serving out data using Databricks SQL. We have a whole load of things to talk through, but we want to hear YOUR questions, which we can field from industry experience, community engagement and internal Databricks direction. There's also a chance we'll get distracted and talk about the Expanse for far too long.

Connect with us: Website: https://databricks.com Facebook: https://www.facebook.com/databricksinc Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/data... Instagram: https://www.instagram.com/databricksinc/