In this session, we will explore the world of small language models, focusing on their unique advantages and practical applications. We will cover the basics of language models, the benefits of using smaller models, and provide hands-on examples to help beginners get started. By the end of the session, attendees will have a solid understanding of how to leverage small language models in their projects. The session will highlight the efficiency, customization, and adaptability of small models, making them ideal for edge devices and real-time applications.

We will introduce attendees to two highly used Small Language Models: Qwen3 and SmolLM3. Specifically, we will cover:

1. Accessing Models: How to navigate HuggingFace to explore and select available models. How to view model documentation and determine its usefulness for specific tasks

2. Deployment: How to get started using

(a) Inference Provider - using HuggingFace inference API or Google CLI

(b) On-Tenant - using Databricks Model Serving

(c) Running the Model Locally - Using Ollama and LMstudio

3. We also examine the tradeoffs of each route

Join Sami Hero and Tammie Coles, as they share how Ellie is reinventing data modeling with AI-native tools that empower both technical and non-technical users. With CData Embedded Cloud, Ellie brings live metadata and data models from systems like Snowflake, Databricks, and Oracle Financials into a unified modeling workspace. Their platform translates legacy structures into human-readable insights, letting users interact with a copilot-style assistant to discover, refine, and maintain data models faster—with less reliance on analysts.

You’ll see how Ellie uses generative AI to recommend new entities, reconcile differences between models and live systems, and continuously document evolving data environments. Learn how corporations are using Ellie and CData together to scale high-quality data modeling across teams. reducing rework, accelerating delivery of analytics-ready models, and making enterprise architecture accessible to the business.

Want to get your GenAI idea noticed? Databricks engineers share their hands-on experiences building interactive demos that actually made business leaders sit up and take notice.

We’ll walk through the journey from a single idea to a working prototype in under a month. Hear how we did it, what worked, what didn’t, including the unexpected hurdles that tripped us up, by taking a practical look at how to:

• Translate technical impact into business value
• Make your voice heard in large dev teams
• Avoid common pitfalls, from permissions to procurement

If you’re a data scientist, engineer, or AI leader who wants to move fast and make your work impossible to ignore, join us to explore how you could create the Minimum Viable Product that makes you the Most Valuable Player.

Large Language Models (LLMs) are transformative, but static knowledge and hallucinations limit their direct enterprise use. Retrieval-Augmented Generation (RAG) is the standard solution, yet moving from prototype to production is fraught with challenges in data quality, scalability, and evaluation.

This talk argues the future of intelligent retrieval lies not in better models, but in a unified, data-first platform. We'll demonstrate how the Databricks Data Intelligence Platform, built on a Lakehouse architecture with integrated tools like Mosaic AI Vector Search, provides the foundation for production-grade RAG.

Looking ahead, we'll explore the evolution beyond standard RAG to advanced architectures like GraphRAG, which enable deeper reasoning within Compound AI Systems. Finally, we'll show how the end-to-end Mosaic AI Agent Framework provides the tools to build, govern, and evaluate the intelligent agents of the future, capable of reasoning across the entire enterprise.

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.

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®

AI agents need seamless access to enterprise data to deliver real value. DataHub's new MCP server creates the universal bridge that connects any AI agent to your entire data infrastructure through a single interface.

This session demonstrates how organizations are breaking down data silos by enabling AI agents to intelligently discover and interact with data across Snowflake, Databricks, BigQuery, and other platforms. See live examples of AI-powered data discovery, real-time incident response, and automated impact analysis.

Learn how forward-thinking data leaders are positioning their organizations at the center of the AI revolution by implementing universal data access strategies that scale across their entire ecosystem.

The entertainment industry is sitting on a huge natural resource: decades of creativity and craftsmanship from talented professionals. Koobrik is an advanced language model designed by, and for, the creative industries. As a Warner Brothers’ accelerator company, the model is already utilised by HBO, A24, DC Comics and many more, to harness ethical artificial intelligence.

Join Koobriks’ CEO and Founder, Orlando Wood, as he shares insights into:

- Building an ethical AI model for the entertainment industry

- The unique challenges of creative data as an asset class

- The AWS and Databricks tech stack powering Koobrik

- Real-world applications, from comic books to screenplays

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®

In today’s landscape, data truly is the new currency. But unlocking its full value requires overcoming silos, ensuring trust and quality, and then applying the right AI and analytics capabilities to create real business impact. In this session, we’ll explore how Oakbrook Finance is tackling these challenges head-on — and the role that Fivetran and Databricks play in enabling that journey.

Oakbrook Finance is a UK-based consumer lender transforming how people access credit. By combining advanced data science with a customer-first approach, Oakbrook delivers fair, transparent, and flexible credit solutions — proving that lending can be both innovative and human-centred.

So you’ve heard of Databricks, but still not sure what the fuss is all about. Yes you’ve heard it’s Spark, but then there’s this Delta thing that’s both a data lake and a data warehouse (isn’t that what Iceberg is?) And then there's Unity Catalog, that's not just a catalog, it also does access management but even surprising things like optimise your data and programmatic access to lineage and billing? But then serverless came out and now you don’t even have to learn Spark? And of course there’s a bunch of AI stuff to use or create yourself. So why not spend 30 mins learning the details of what Databricks does, and how it can turn you into a rockstar Data Engineer.

Large Language Models (LLMs) are transformative, but static knowledge and hallucinations limit their direct enterprise use. Retrieval-Augmented Generation (RAG) is the standard solution, yet moving from prototype to production is fraught with challenges in data quality, scalability, and evaluation.

This talk argues the future of intelligent retrieval lies not in better models, but in a unified, data-first platform. We'll demonstrate how the Databricks Data Intelligence Platform, built on a Lakehouse architecture with integrated tools like Mosaic AI Vector Search, provides the foundation for production-grade RAG.

Looking ahead, we'll explore the evolution beyond standard RAG to advanced architectures like GraphRAG, which enable deeper reasoning within Compound AI Systems. Finally, we'll show how the end-to-end Mosaic AI Agent Framework provides the tools to build, govern, and evaluate the intelligent agents of the future, capable of reasoning across the entire enterprise.

In today’s fragmented data landscape, organisations are under pressure to unify their data estates while maintaining agility, governance, and performance. This session explores how Microsoft Fabric, OneLake, and Azure Databricks come together to deliver a powerful, open, and integrated platform for centralised data orchestration—without compromise. From ingestion to insight, this session will showcase how “no excuses” becomes a reality when your data is truly unified, with a real-time demonstration highlighting the platform’s capabilities in action.

In this session, we will explore how organisations can leverage ArcGIS to analyse spatial data within their data platforms, such as Databricks and Microsoft Fabric. We will discuss the importance of spatial data and its impact on decision-making processes. The session will cover various aspects, including the ingestion of streaming data using ArcGIS Velocity, the processing and management of large volumes of spatial data with ArcGIS GeoAnalytics for Microsoft Fabric, and the use of ArcGIS for visualisation and advanced analytics with GeoAI. Join us to discover how these tools can provide actionable insights and enhance operational efficiency.