Your AI is only as good as your data. Downtime, pipeline failures, and blind spots threaten revenue, compliance, and trust. Join Acceldata at Big Data London to explore Agentic Data Management (ADM), where AI agents autonomously resolve issues, optimize pipelines, and ensure governance. Powered by xLake Reasoning Engine, ADM delivers trusted, AI-ready data with self-healing operations. Hear how enterprises like Dun & Bradstreet boosted reliability and compliance. Ideal for data leaders, engineers, architects, analysts, product managers, and governance heads seeking autonomous data excellence. Visit Booth M70 for live demos

In this 20-minute session, you'll learn how to build a custom Fivetran connector using the Fivetran Connector SDK and the Anthropic Workbench (AI Assistant) to integrate data from a custom REST API into Snowflake. 

You'll then learn how to create a Streamlit in Snowflake data application powering metrics and Snowflake Cortex AI-driven applications.

Enterprises are eager to realise the promise of AI—from insights to decisions to automation. The business is ready to innovate, but fragmented data, rigid AI governance, and the cost and complexity of AI innovation just create frustration. 

This session explores a bold idea: the business—not IT—will lead AI innovation. Success depends on enabling teams to ideate freely, experiment rapidly, and unlock new value at market pace. We’ll discuss how a modern data product strategy empowers business teams with access, trust, and agility—so they can test ideas quickly and scale what works.

You’ll learn why experimentation is the new strategic advantage—and how to turn business curiosity into competitive impact.

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.

Three out of four companies are betting big on AI – but most are digging on shifting ground. In this $100 billion gold rush, none of these investments will pay off without data quality and strong governance – and that remains a challenge for many organizations. Not every enterprise has a solid data governance practice and maturity models vary widely. As a result, investments in innovation initiatives are at risk of failure. What are the most important data management issues to prioritize? See how your organization measures up and get ahead of the curve with Actian.

Without strong governance, AI rests on shaky ground. See the data priorities that turn risk into reliable business outcomes.

In today’s AI-driven world, data is your most powerful asset—but only if it’s trusted, secure, and well-governed. Join Microsoft sales leaders for a fast-paced panel exploring how UK organisations are laying strong data foundations to unlock real business impact. From securing sensitive information to navigating governance and compliance, hear what’s resonating in the UK market and how customers are turning data into competitive advantage. 

A leading rheumatologist teamed up with an AI specialist to help with a systematic review of lupus research, a condition of which 90% of patients are women. Together, they revealed the deep-rooted biases in research methodologies - and the machine learning models that underpin them.

Professor Coziana Ciurtin (UCL) and Mirela Gyurova (Kubrick) share the story behind their GenAI tool which can revolutionise underfunded and underexplored areas of medical research, including identifying ML-enforced biases.

When gender and ethnic disparities in healthcare persist, what responsibilities do data professionals have in shaping ethical, impactful AI? And how can partnerships between industry and academia unlock new standards for evidence, equity, and trust in ML?

For anyone building, using, or regulating AI, this session will challenge assumptions and make the case for responsible, cross-sector innovation.

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AI is redefining what’s possible in energy; accelerating innovation, enhancing decision-making, and opening new frontiers of efficiency and performance. In this fireside chat, SLB will share how they’re empowering customers to capture new value through AI-powered innovation, accelerating AI skillsets and capabilities in the workforce, and navigating the next horizon of agentic AI solutions.

Joseph Toma is the Cloud and AI Director for Media and Communications. Joseph’s career spans across enterprise, scale-up, and start-up environments, most notably as the CEO of Jugo, an innovative AI SaaS platform. His tenure as Managing Partner at Kyndryl and various leadership roles at IBM, including Hybrid Cloud and Red Hat Sales Director, took him to three continents and has equipped him with a unique perspective that shapes his approach to supporting customers. Joseph is based in London where he lives with his wife, young child, and cavapoo.

How Generative AI dynamically transforms business problems into executable graphs of data products, by creating AI-powered digital twins. Describing business needs in plain language and generating and simulate entire end to end business processes with UX as an interconnected eco-system as graph data products, demonstrated through real-world use-cases.

https://www.bigdataldn.com/en-gb/conference/session-details.4500.251876.building-an-ai_ready-open-lakehouse-on-google-cloud.html

Discover how to build a powerful AI Lakehouse and unified data fabric natively on Google Cloud. Leverage BigQuery's serverless scale and robust analytics capabilities as the core, seamlessly integrating open data formats with Apache Iceberg and efficient processing using managed Spark environments like Dataproc. Explore the essential components of this modern data environment, including data architecture best practices, robust integration strategies, high data quality assurance, and efficient metadata management with Google Cloud Data Catalog. Learn how Google Cloud's comprehensive ecosystem accelerates advanced analytics, preparing your data for sophisticated machine learning initiatives and enabling direct connection to services like Vertex AI. 

From broken pipelines to hallucinating agents, reliability challenges are the hidden hurdles blocking AI success. Learn how leading enterprises are using observability to detect anomalies, triage incidents, and operationalize trust across their entire data + AI stack.

In this session, Omni CEO Colin Zima and VP of Product Arielle Strong will share how early experiments led to AI features our customers actually use and love: from natural language chat, to embeddable AI products, to APIs and an MCP server. 

They’ll walk through what worked, what didn’t, and how AI has reshaped our product roadmap. Expect real-world examples of AI analytics in production, along with best practices for getting your data AI-ready.

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.

Data contracts bring clarity to governance. See how they cut defects, speed AI onboarding, and reduce compliance risks.

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. 

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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.