With the pace of change of AI being experienced across the industry and the constant bombardment of contradictory advice it is easy to become overwhelmed and not know where to start. 

The promise of LLMs have been undermined by vendor and journalistic hype and an inability to rely on quantitative answers being accurate. Afterall, what good would a colleague be (artificial or not) if you already need to know the answer to validate any question that you ask of them?

The promise of neuro-symbolic AI that combines two well established technologies (semantic knowledge graphs with machine learning) enable you to get more accurate LLM powered analytics and most importantly faster time to greater data value.

In this practical, engaging and fun talk, Ben will equip you with the principles and fundamentals that never change but often go under-utilised, as well as discussing and demonstrating the latest techniques, platforms and tools so that you can get started with confidence.

Ben will show that far from taking months, data products can take minutes or hours to prepare, publish and start gaining value from, all in a sustainable and maintainable manner.

When Virgin Media and O2 merged, they faced the challenge of unifying thousands of pipelines and platforms while keeping 25 million customers connected. Victor Rivero, Head of Data Governance & Quality, shares how his team is transforming his data estate into a trusted source of truth by embedding Monte Carlo’s Data + AI Observability across BigQuery, Atlan, dbt, and Tableau. Learn how they've begun their journey to cut data downtime, enforced reliability dimensions, and measured success while creating a scalable blueprint for enterprise observability.

75% of GenAI projects fail to scale—not because the models lack sophistication, but because they’re built on fragmented data. If your systems don’t know who they're talking about, how can your AI deliver reliable insights?

This talk unveils how real-time Entity Resolution (ER) is becoming the silent engine behind trusted, AI-ready data architecture. We will discuss how organizations across financial services, public safety, and digital platforms are embedding ER into modern data stacks—delivering identity clarity, regulatory confidence, and faster outcomes without the drag of legacy MDM.

You’ll learn:

• Why ER is foundational for AI trust, governance, and analytics
• Patterns for embedding ER into streaming and event-driven architectures
• How ecosystem partners and data platforms are amplifying ER value
• How to build trust at the entity level—without slowing down innovation

Whether you’re modernizing architecture, launching AI programs, or tightening compliance, this session will equip you to embed trust from the ground up.

We are entering an Age of Artificial Intelligence with unprecedented opportunities. Companies are integrating AI-driven solutions to enhance efficiency, drive innovation, and maintain a competitive edge. However, prevailing myths about AI create uncertainty in strategic decision-making and adoption. We will discuss four foundational myths in our AI centric world: 1) regulation is an innovation killer; 2) scaling current models will lead to Artificial General Intelligence (AGI); 3) general models create maximum value; and 4) the value of data is unlimited. We will show these myths are delaying AI progress and provide research in overcoming their challenges.

As AI systems become increasingly agentic - acting with more autonomy, initiative, and influence - the need for a new kind of human leadership has never been greater. Technology may accelerate decisions, but it cannot set direction, build trust, or inspire people to change. That’s the role of agentic leadership: intentional, visible, and human-centred. 

Drawing on both current research and her experience leading global data programmes and coaching senior executives, Helen Mannion will show why organisations must evolve their leadership as much as their technology. 

Attendees will leave with clear insight into how they can accelerate AI adoption in organisations, the specific leadership behaviours that make the biggest difference, and practical steps they can take to start building the conditions for AI to succeed.

Join Amperity’s Marcus Owens, Lead Solution Consultant, to learn more about the rapid innovations in data architecture brought by the new wave of AI agents. This session will start with a quick overview of what makes a good AI Agent – and then focus on how Agentic strategies can accelerate two key needs in customer data: 

Make Customer Data Usable – How AI Agents accelerate customer data engineering with Amperity’s Stitch and Chuck Data – saving data engineering teams hundreds of hours of effort. 

Make Use of Customer Data – How AmpAI allows Marketers to build outcome-driven customer journeys, going from intent to results faster than ever before.

Arch Capital Group, a $34 billion S&P 500 specialty insurance leader managing $21.5 billion in gross premiums across 60+ global offices, faced a critical challenge: ensuring data quality and consistency across their complex risk assessment operations. With 25+ predictive models supporting AI-driven underwriting for specialty lines—the industry's most complex and unusual risks—incomplete or inaccurate data inputs threatened the accuracy of critical business decisions spanning property & casualty, reinsurance, and mortgage insurance operations. 

In this session, Sam from Arch Capital shares how the organization partnered with DQLabs to transform their data trust framework, implementing automated quality checks across their global data ecosystem. Learn how this transformation enabled Arch to maintain their disciplined underwriting approach while scaling operations, improve regulatory compliance across multiple jurisdictions, and enhance their ability to respond rapidly to emerging risks while supporting the data accuracy essential for their leadership position in specialty insurance markets.

Abstract:AI promises transformation, but most enterprises are still held back by a blind spot: unstructured data. The documents, conversations, and content that hold the richest business insights remain locked away—unusable, ungoverned, and invisible to AI. This untapped treasure delays projects, derails accuracy, and creates governance risks.

In this exclusive launch session, Teresa Rojas, Senior Director of Product Management at Collibra, and Reece Griffiths, co-founder of Deasy Labs (now part of Collibra), will unveil Collibra Unstructured AI. They’ll show how breakthrough technology, combined with Collibra’s unified governance platform, enables organizations to finally move beyond the black box and unlock the hidden wealth in their data to power trustworthy, scalable AI.

AI is no longer a lab experiment; it’s reshaping how business gets done. This session explores how Rackspace is integrating AI agents as teammates, rather than technology tools. Learn how to cut through industry groupthink, redesign workflows, and build a new operating model where humans and AI collaborate to drive trust, growth, and resilience.

On average, one woman is killed by an abusive partner or ex every five days in England and Wales (Refuge).  

Clare’s Law, introduced in 2014, was intended to help prevent such tragedies, allowing Police to proactively disclose domestic violence history to victims potentially at risk. Yet while the law gave the Police new powers, officers’ capacity could inhibit efficient response to these requests - with siloed data across systems making proactively identifying safeguarding risks a challenge.

Bedfordshire Police, in partnership with Palantir, has built a solution to address these challenges - harnessing AI and big data to transform their force’s safeguarding approach from reactive to proactive, enabling faster identification and safeguarding of those at risk.

Emily Fitzsimons (Deployment Strategist, Palantir) alongside Bedfordshire Police will explore the challenges created for Police Public Protection Units by an increasingly complex data landscape - and how they're using latest technologies like AI to overcome them.

Join us to see how we're transforming safeguarding to help reduce domestic violence by empowering potential victims with vital information before it's too late.

Powered by Women in Data®

AI may be the enabler, but people are the driving force. From ethical design and cultural transformation to trust-building and team diversity, the session examines how people power progress.

This 30-minute discussion curated by Women in Data® brings together senior data leaders from Legal & General, M&G and Faculty, to explore how a human-centric mindset is essential for delivering responsible, impactful AI in financial services.

Speakers will share real-world insights into leading change, embedding inclusive practices, and turning complex data into meaningful outcomes. Expect a fast-paced, thought-provoking dialogue that reframes AI as not just smart tech, but a tool that must be shaped by empathy, purpose, and collaboration.

Powered by: Women in Data®

Sound AI outcomes start with trusted, high-quality data and delivering it efficiently is now a core part of every data and AI strategy. In this session, we’ll discuss how AI-supportive capabilities such as autonomous data catalogs, unstructured metadata ingestion and automated data trust scoring are transforming how organizations deliver AI-ready data products at scale with less hands-on staff involvement.

You’ll see how GenAI and agentic AI can accelerate reliable data delivery at every stage, from identifying and fixing data issues to building semantic business layers that give your AI models the context-rich inputs needed for success. We’ll also explore how agentic AI enables self-updating catalogs, proactive data quality monitoring, and automated remediation to free your teams to focus on innovation instead of maintenance.

If you’re shaping your organization’s data and AI strategy as a CDO, CDAIO, CIO, or data leader, this is your blueprint to operationalizing trusted, governed, and AI-ready data for every initiative, faster and smarter.

I don’t like it. I don't get it. I don’t trust it.' 

Sounds familiar?

Even with the best Data and AI tools, organisations struggle to see results if their people don’t engage. Change is hard, and without attention to mindset and culture, even the most sophisticated Data and AI initiatives can fall short.

Rosanne Werner, CEO of XcelerateIQ, previously led the multi-award winning Data and AI Mindset and Culture programme at Coca-Cola Europacific Partners, reaching over 2,000 participants worldwide.

In this session, we’ll explore how to ‘Crack the Human Firewall’ with a science-based approach to Data and AI mindset and culture. 

You’ll learn:

• How the brain changes and learns - and how to use this to enable Data and AI acceptance.

• How to rewire habits to integrate Data and AI into daily workflows.

• How to use social dynamics to build a collective mindset that advocates for Data and AI.

Proven by science - Let's help your teams put Data and AI into Action!

SAP Business Data Cloud is a fully managed solution that unifies and governs all SAP data while seamlessly integrating with third-party sources. With SAP Business Data Cloud, organisations can accelerate decision-making by empowering business users to make more impactful choices. It also provides a trusted foundation for AI, ensuring that data across applications and operations is reliable, responsible, and relevant—enabling organisations to harness the full potential of generative AI.

Site Reliability Engineers spend countless hours diagnosing complex production issues and optimizing system performance. This talk explores how Large Language Models can augment SRE workflows with real-world examples.

We'll also demonstrate live tooling that leverages AI to optimize database configurations - automatically recommending ordering keys, generating materialized views, and suggesting performance improvements based on query patterns and system metrics.

Rather than theoretical possibilities, this talk focuses on practical implementations with measurable results. Attendees will learn actionable strategies for integrating LLMs into their SRE workflows, understand the current boundaries of AI effectiveness in operations, and see concrete examples of tooling already delivering value in production environments.

Everyone’s talking about GenAI. But at Big Data London, you want more than hype. 

In this session, Simon Devine (Founder of Hopton Analytics) shares how the East of England Co-op embedded GenBI – Pyramid’s generative AI tool – into their business intelligence platform to improve how decisions are made across the organisation. 

This wasn’t a flashy experiment. It was a carefully planned rollout of AI-generated explanations, natural language querying, and explainable analytics – designed to support busy operational teams, reduce report backlogs, and drive smarter decisions at scale. 

Simon will take you behind the scenes of the project: how it was planned, what hurdles had to be overcome, and the governance structures that helped it succeed. You'll hear honest reflections on what worked, what didn’t, and what they’d do differently.

 Whether you’re a data leader looking for real-world use cases, a BI owner exploring GenAI adoption, or a transformation lead trying to unlock value from your reporting stack – this session will give you practical insight, not just theory.

 Come for the lived experience. Leave with ideas you can actually use.

How do you deliver reliable data across dozens of countries, diverse tech stacks, and constantly evolving use cases? In this session, Vinicio Oliviera, Senior Data Platform Manager at Delivery Hero, shares how his team ensures trust in data at scale. From real-time sales streams to AI-driven vendor insights, he’ll show how Delivery Hero uses Monte Carlo’s monitoring-as-code to unify reliability across regions, balance central standards with local autonomy, and keep data powering decisions around the globe.

AI is rewriting the recruitment rulebook with the potential to make it smarter, fairer and more efficient, but it is not without its challenges. In this 30-minute session, leading Women in Data® experts from AXA, Munich Re, Royal London, Thatcham Research and Virgin Media O2 unpack the real-world impact of AI on hiring practices.  

Our panel will share how they are responding to the rise of AI-generated profiles, the growing cost of candidate screening and the responsibility to maintain transparency and trust at all stages. Expect practical insights and honest reflections on what it takes to proactively utilise AI responsibly, and effectively, in recruitment today.

Powered by: Women in Data®

AI is only as good as the data it runs on. Yet Gartner predicts in 2026, over 60% of AI projects will fail to deliver value - because the underlying data isn’t truly AI-ready. “Good enough” data isn’t enough.

In this exclusive BDL launch session, DataOps.live reveal Momentum, the next generation of its DataOps automation platform designed to operationalize trusted AI at enterprise scale.

Based on experiences from building over 9000 Data Products to date, Momentum introduces breakthrough capabilities including AI-Ready Data Scoring to ensure data is fit for AI use cases, Data Product Lineage for end-to-end visibility, and a Data Engineering Agent that accelerates building reusable data products. Combined with automated CI/CD, continuous observability, and governance enforcement, Momentum closes the AI-readiness gap by embedding collaboration, metadata, and automation across the entire data lifecycle.

Backed by Snowflake Ventures and trusted by leading enterprises, including AstraZeneca, Disney and AT&T, DataOps.live is the proven catalyst for scaling AI-ready data. In this session, you’ll unpack what AI-ready data really means, learn essential practices, discover a faster, easier, and more impactful way to make your AI initiatives succeed.

Be the first to see Momentum in action - the future of AI-ready data.

Insights on how to generate real value with AI, treat data as a product, and the state of data products today.

Paradime is the pioneer in building the 'Cursor for Data' - a platform for the AI-enabled analytics engineer to achieve 10x productivity. In this lighting talk, we will showcase how Paradime and DinoAI is changing the way analytics engineering is done.

In the era of AI agents, data products, and exploding complexity, enterprises face an unprecedented challenge: how to give machines and people, the context needed to make decisions that are accurate, explainable, and trustworthy. 

What if data teams could solve this? 

We'll explore a new opportunity: data teams as the architects and stewards of the “Enterprise Brain”, a unified knowledge layer that connects business concepts, data, and processes across the organization. By treating context as a first-class citizen, organizations can bridge structured and unstructured worlds, govern data and AI agents effectively, and unlock faster, more confident decision-making. 

We'll unpack: 

• Why context and knowledge are becoming the missing pieces of AI readiness. 

• How structured and unstructured data are converging, and why this demands a new governance model. 

• Why ontologies, knowledge graphs, and active governance are critical to managing the coming explosion of AI agents. 

• The unique chance data teams have right now to lead and move from building pipelines to building the enterprise brain. 

We won’t talk tools. We’ll talk possibility. By the end, you’ll see why the most successful organizations of the next decade will be the ones who make their data teams the creators and owners of knowledge itself. 

What the rest of the world can learn from gaming’s data-first approach to AI adoption.

Gaming pioneered many of the AI foundations we rely on today, from GPUs to reinforcement learning. It continues to drive innovation, but it has also built a strong resistance to hype. This session explores how gaming teams evaluate, deploy, and reject AI solutions with a discipline other industries can learn from.

This talk will explore how NVIDIA Blueprints are accelerating AI development and deployment across various industries, with a focus on building intelligent video analytics agents. Powered by generative AI, vision-language models (VLMs), large language models (LLMs), and NVIDIA NIM Microservices, these agents can be directed through natural language to perform tasks such as video summarization, visual question answering, and real-time alerts. This talk will show how VSS accelerates insight from video, helping industries transform footage into accurate, actionable intelligence.

As organizations increasingly adopt AI and data-driven strategies, ensuring quality and reliability across the entire data + AI estate has never been more critical. This session will explore 2026 as the year of Data + AI Observability, highlighting key trends driving this transformation. Attendees will gain insights into how observability bridges the gap between data and AI systems across your data, system, code, and models, enabling more trustworthy, scalable, and efficient operations. Join us to learn practical approaches and tools that can future-proof your data and AI initiatives to drive real business impact.