As enterprises scale their deployment of Generative AI (Gen AI), a central constraint has come into focus: the primary limitation is no longer model capability, but data infrastructure. Existing platforms, optimized for human interpretation and batch-oriented analytics, are misaligned with the operational realities of autonomous agents that consume, reason over, and act upon data continuously at machine scale. 

In this talk, Zhamak Dehghani — originator of the Data Mesh and a leading advocate for decentralized data architectures — presents a framework for data infrastructure designed explicitly for the AI-native era. She identifies the foundational capabilities required by Gen AI applications: embedded semantics, runtime computational policy enforcement, agent-centric, context-driven discovery.

The session contrasts the architectural demands of AI with the limitations of today’s fragmented, pipeline-driven systems—systems that rely heavily on human intervention and customized orchestration. Dehghani introduces autonomous data products as the next evolution: self-contained, self-governing services that continuously sense and respond to their environment. She offers an architectural deep dive and showcases their power with real-world use cases.  

Attendees will learn the architecture of “Data 3.0”, and how to both use GenAI to transform to this new architecture, and how this new architecture serves GenAI agents at scale.

Maximize the value of your SAP investments by harnessing the power of Data and AI on Azure. In this session, you’ll learn proven strategies to leverage SAP landscapes, unify data across SAP and non-SAP systems, and unlock advanced analytics with Azure’s Agentic AI capabilities. We’ll showcase industry-ready accelerators that accelerate transformation, enable governed data access, and turn insights into action to fuel innovation, agility, and measurable business outcomes.

This presentation provides an overview of how NVIDIA RAPIDS accelerates data science and data engineering workflows end-to-end. Key topics include leveraging RAPIDS for machine learning, large-scale graph analytics, real-time inference, hyperparameter optimization, and ETL processes. Case studies demonstrate significant performance improvements and cost savings across various industries using RAPIDS for Apache Spark, XGBoost, cuML, and other GPU-accelerated tools. The talk emphasizes the impact of accelerated computing on modern enterprise applications, including LLMs, recommenders, and complex data processing pipelines.

While 95% of enterprise AI pilots fail to deliver business value, Secoda's customers are seeing a different reality: with 76% of AI usage focused on core business intelligence workflows rather than isolated experiments. 

Join Etai Mizrahi, Co-Founder & CEO of Secoda, as he shares how companies like Dialpad achieved company-wide AI adoption by moving 200+ employees from traditional dashboards to natural language analytics. Learn how Secoda's multi-agent AI architecture transforms data governance from manual overhead into automated workflows, and learn practical strategies for scaling AI beyond pilots to become essential infrastructure that delivers measurable ROI.

Today’s shifting security dynamics call for data-driven insights that pre-empt dangers and guide swift, informed choices.

In this joint session led by commercial and public defence experts, we’ll unpack how cutting-edge AI solutions and flexible data platforms illuminate operations across land, sea, air, and cyber.

Join us to hear how these methods can be applied in any fast-paced setting to amplify adaptability, strengthen safeguards, and outpace new challenges.

Powered by: Women in Data®

DfE are providing schools and local authorities with world-leading MI and intelligent reporting to take early action and help pupils thrive. With a national view of data, and through collaboration, system integration, smart analytics and responsible AI, we make it easier to spot issues, understand context and drive down absence.

Powered by: Women in Data®

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.

For nearly 200 years, Dun & Bradstreet has supported clients in achieving growth through the transformative power of data and analytics. As the world has rapidly evolved, so have we—serving more industries in more places than ever. We combine global data with local expertise to provide deep insights, intelligent tools, and tailored solutions. From navigating economic challenges to capitalising on new opportunities, we help businesses make smarter decisions and unlock value throughout every phase of the business lifecycle.

Powered by Women in Data®

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.

What does it really mean to be a data-driven organisation? In this session, Hazal Muhtar, Senior Director of Analytics at Wise, will share real-life examples of how customer data fuels product innovation, marketing and growth at one of the world’s leading fintech companies.

Hazal will explore how data is driving change across industries and reshaping the way businesses operate. She’ll also discuss the importance of data democratization—how winning teams across an organisation access to insights can spark innovation, accelerate decision-making and build a culture where data is a shared language.

Join this session to discover how Wise embraces data at scale, and leave with practical takeaways on how customer data can become your most powerful asset in unlocking transformation and growth.

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.

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.

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.

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.

Learn how to transform your data warehouse for AI/LLM readiness while making advanced analytics accessible to all team members, regardless of technical expertise. 

We'll share practical approaches to adapting data infrastructure and building user-friendly AI tools that lower the barrier to entry for sophisticated analysis. 

Key takeaways include implementation best practices, challenges encountered, and strategies for balancing technical requirements with user accessibility. Ideal for data teams looking to democratize AI-powered analytics in their organization.

In travel, every second counts and missed signals can mean missed opportunities. This expert panel of Women in Data® leaders will explore how real-time analytics is reshaping decision-making across the travel industry at every stage, from streamlining internal operations to improving the passenger experience.  

Whether you're taking your proverbial first steps or are light years ahead leading your own data team, we can guarantee there will be something for everyone to connect to and reflect on whilst also discovering how live insights are helping drive data-led decision makers to act faster, smarter, and with greater impact.

Powered by Women in Data®

Legacy data tools weren’t built for the AI era. Agentic Data Management replaces static rules and siloed platforms with intelligent agents that monitor, reason, and act—automating quality, governance, and lineage at scale. Discover how data leaders are shifting from manual firefighting to autonomous control, powering faster, trusted, and scalable data for AI and analytics.

- See a live demo of an agentic system in action

- Learn how probabilistic and deterministic approaches work in concert

- Explore how to build intelligent data products using the MCP protocol

As enterprises scale their deployment of Generative AI (Gen AI), a central constraint has come into focus: the primary limitation is no longer model capability, but data infrastructure. Existing platforms, optimized for human interpretation and batch-oriented analytics, are misaligned with the operational realities of autonomous agents that consume, reason over, and act upon data continuously at machine scale. 

In this talk, Zhamak Dehghani — originator of the Data Mesh and a leading advocate for decentralized data architectures — presents a framework for data infrastructure designed explicitly for the AI-native era. She identifies the foundational capabilities required by Gen AI applications: embedded semantics, runtime computational policy enforcement, agent-centric, context-driven discovery.

The session contrasts the architectural demands of AI with the limitations of today’s fragmented, pipeline-driven systems—systems that rely heavily on human intervention and customized orchestration. Dehghani introduces autonomous data products as the next evolution: self-contained, self-governing services that continuously sense and respond to their environment. She offers an architectural deep dive and showcases their power with real-world use cases.  

Attendees will learn the architecture of “Data 3.0”, and how to both use GenAI to transform to this new architecture, and how this new architecture serves GenAI agents at scale.

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.

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.

Business leaders are demanding clear evidence that data investments are generating real business value — not just summaries of how many dashboards or datasets live in your analytics environment. This session will equip you with practical, proven methods — like business value maps and usage analytics — to uncover, measure, and clearly communicate the true business impact of your data and analytics initiatives. You’ll leave with the tools and language you need to lead ROI conversations, defend your strategy, and secure ongoing investment.

In an era where data drives decisions, Knight Frank is redefining what it means to be in property with purpose. This session explores how Knight Frank harnesses the power of big data not just to optimise real estate strategies, but to create meaningful social impact across communities. From urban regeneration to inclusive housing initiatives, data is at the heart of their mission to build a better future.

A key highlight of the talk will be Knight Frank’s collaboration with Girls in Data, a pioneering initiative aimed at empowering young women to pursue careers in data and analytics. Through mentorship, workshops, and hands-on experience, Knight Frank is helping to close the gender gap in tech and foster the next generation of data leaders.

Join us to discover how data can be a force for good, driving equity, opportunity, and transformation in the property sector and beyond.

Powered by: Women in Data®

How do you prepare a global industrial business for AI? At Secil, the answer was data governance. In this session, Ricardo Carvalho shares how the team replaced siloed systems with a unified data platform using Domo, delivering enterprise-level analytics, smarter operations, and a foundation for scalable AI that drives real outcomes in just 18 months.

In an era where data is central to business success, the demand for skilled analysts continues to outpace supply. This session explores how data analytics apprenticeships offer a dynamic, practical solution to the widening skills gap, equipping individuals with industry-relevant experience while delivering immediate value to employers.

Using the NowSkills apprenticeship model as a case study, this session will showcase how a well-rounded curriculum—combining technical training, real-world projects, and structured mentorship—can transform aspiring analysts into confident, capable professionals. Attendees will gain insights into how these programmes adapt to diverse learning needs, integrate business challenges, and embed workplace-ready skills from day one.

Through success stories and data-driven outcomes, the presentation will highlight the benefits for both individuals and organisations: from faster onboarding and increased employee engagement to improved innovation and retention. Additionally, apprenticeships contribute to greater diversity and inclusion by widening access to digital careers beyond traditional academic routes.

Attendees will leave with practical strategies to implement or enhance apprenticeship programmes, identify future skills, and collaborate effectively

Data is one of the most valuable assets in any organisation, but accessing and analysing it has been limited to technical experts. Business users often rely on predefined dashboards and data teams to extract insights, creating bottlenecks and slowing decision-making.

This is changing with the rise of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). These technologies are redefining how organisations interact with data, allowing users to ask complex questions in natural language and receive accurate, real-time insights without needing deep technical expertise.

In this session, I’ll explore how LLMs and RAG are driving true data democratisation by making analytics accessible to everyone, enabling real-time insights with AI-powered search and retrieval and overcoming traditional barriers like SQL, BI tool complexity, and rigid reporting structures.