talk-data.com talk-data.com

Topic

Big Data

data_processing analytics large_datasets

16

tagged

Activity Trend

28 peak/qtr
2020-Q1 2026-Q1

Activities

Showing filtered results

Filtering by: Big Data LDN 2025 ×

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®

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.

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.

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®

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

If you want to scare a Data Engineer with four words, ‘big data, high concurrency’ will probably do it. As data moved from the realm of BI reporting to being a customer-facing commodity, serving huge volumes of data to thousands of unforgiving app users is no small challenge. In this session, Connor Carreras will share (and demo!) how a major martech platform uses Firebolt to serve data about millions of websites to their worldwide customers with consistent millisecond response times. After this session, you will know how you can build low-latency data applications yourself. You’ll also have a deep understanding of what it takes for modern high-performance query engines to do well on these workloads.

Face To Face
by Gavi Regunath (Advancing Analytics) , Simon Whiteley (Advancing Analytics) , Holly Smith (Databricks)

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.

Join us for an unmissable evening of insight, discussion, and lively debate at The High Performance Data and AI Debate, hosted by Chris Tabb — a unique Big Data London special running from 6:00–8:00 PM. This fast-paced, interactive event brings together some of the brightest minds in data and AI to tackle the most pressing questions shaping the future of teams, architecture, and products in an AI-first world.

The evening kicks off at 6:00 PM with a welcome and free drinks. Then, across three rapid-fire 20-minute debates, our expert panels will explore:

AI & Data – Teams (Chair: Eevamaija Virtanen)

Mehdi Ouazza, Paul Rankin, Jesse Anderson, Hugo Lu

AI & Data – Architecture (Chair: Adi Polak)

Chris Freestone, David Richardson, Nick White, Karl Ivo Sokolov

AI & Data – Products (Chair: Jai Parmar)

Kelsey Hammock, Jean-Georges (jgp) Perrin, Taylor McGrath, Jon Cooke

Refuel with free pizza at 6:50 PM, then stay for the Town Hall Debate, where all speakers return to the stage for an open-floor Q&A — your chance to challenge their ideas, share perspectives, and shape the conversation.

Expect fresh perspectives, healthy disagreement, and practical takeaways you can bring back to your organisation. Whether you’re leading a data team, designing cutting-edge architectures, or building AI-powered products, this is your space to engage with the people shaping what’s next.

Face To Face
by Jeremiah Stone (snapLogic) , Dr Mary Osbourne (SAS) , Mike Ferguson (Big Data LDN) , David Kalmuk (IBM Core Software) , Chris Aberger (Alation) , Vivienne Wei (Salesforce)

In this, the 10th year of Big Data LDN, in its flagship Great Dat Debate keynote panel, conference chair and leading industry analyst Mike Ferguson welcomes executives from leading software vendors to discuss key topics in data management and analytics. Panellists will debate the challenges and success factors in building an agentic enterprise, the importance of unified data and AI governance, the implications of key industry trends in data management, how best to deal with real-world customer challenges, how to build a modern data and analytics (D&A) architecture, and issues on-the-horizon that companies should be planning for today.

Attendees will learn best practices for data and analytics implementation in a modern data and AI -driven enterprise from seasoned executives and an experienced industry analyst in a packed, unscripted, candid discussion.

Last year, Big Data London’s GenAI theatres were packed. Fast forward 12 months, and AI is everywhere. So, this AI lark is easy now… right?  

 

Lifting the lid on the AI bubble, reality is starting to bite. AI initiatives are stalling, models are drifting, and demonstrating tangible business value is really hard. Why? Because we’ve all sprinted into the AI future without first packing the essentials: high-quality, trusted data; a shared language for decision-making; solid governance; and the skilled people to make it all work.  

 

In 2025, the organisations that will see the best returns from their AI programs are those that have gone back to the future by pressing rewind to get their data foundations right before scaling the shiny stuff.  

 

Join Andy Crossley, CTO at Oakland, alongside Alex Pearce, Chief Microsoft Strategist at Softcat, for a no-holds-barred conversation about the realities of AI in practice.  

 

Lifting the lid on:  

 

Why so many AI projects fail to deliver real value  

 

The critical data foundations every business needs to succeed  

 

Real-world lessons from organisations discovering that AI is far more complex than the hype suggests  

 

The good news? You’ll leave with practical, actionable steps to start unlocking value from your AI investments.  

 

We can’t promise all the answers, but this session will reassure you that you are not alone. We aim to inspire new thinking and provide the guidance you need to navigate the most common pitfalls on the path to making AI work for you. 

To explore how the University of Oxford leverages a unified approach to high-performance computing infrastructure and scalable data platforms across the Big Data Institute and the Centre for Human Genetics to advance biomedical research across the entire University.

This session will discuss:

  • Breakthroughs enabled by HPC and secure data platforms in health research
  • Infrastructure needs for biomedical innovation and large-scale data science
  • Oxford’s partnership journey with Dell Technologies and NVIDIA and its real-world impact
  • How scalable AI infrastructure is accelerating research outcomes

DuckDB is well-loved by SQL-ophiles to handle their small data workloads. How do you make it scale? What happens when you feed it Big Data? What is this DuckLake thing I've been hearing about? This talk will help answer these questions from real-world experience running a DuckDB service in the cloud.

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.

In an era where data complexity and scale challenge every organization, manual intervention can no longer keep pace. Prizm by DQLabs redefines the paradigm—offering a no-touch, agentic data platform that seamlessly integrates Data Quality, Observability, and Semantic Intelligence into one self-learning, self-optimizing ecosystem.

Unlike legacy systems Prizm is AI native, it is Agentic by Design, built from the ground up around a network of intelligent, role-driven agents that observe, recommend, act, and learn in concert to deliver continuous, autonomous data trust.

Join us at Big Data London to Discover how Prizm’s agent-driven anomaly detection, data quality enforcement, and deep semantic analysis set a new industry standard—shifting data and AI trust from an operational burden to a competitive advantage that powers actionable, insight-driven outcomes.

Face To Face
by Aaron Baker (Multiverse) , Jane Crowe (UK Ministry of Defence) , Kash Nejad (Multiverse)

Multiverse is proud to host the Ministry of Defence (MOD) on stage at Big Data LDN to discuss their pioneering partnership focused on building data skills and capabilities across the defence sector. As organisations worldwide navigate the transformative potential of AI and advanced analytics, investing in staff development has become a strategic imperative. This partnership is already making tangible impact: over 250 MOD employees are currently enrolled in upskilling programmes designed to strengthen data literacy, enhance analytical capabilities, and embed a culture of continuous learning. The initiative equips personnel to leverage data effectively, driving smarter decision-making and supporting the MOD’s ongoing Strategic Defence Reform agenda.

Speakers will share insights into how targeted learning interventions and personalised development pathways can accelerate organisational capability while delivering measurable outcomes. Attendees will hear first-hand how the collaboration between Multiverse and the MOD has delivered early successes, fostered a growth mindset among staff, and positioned the MOD to scale these programmes far beyond their current reach. This session offers a unique opportunity for leaders and practitioners alike to explore the intersection of talent investment, AI adoption, and data-driven transformation, demonstrating how strategic upskilling can future-proof organisations in an increasingly complex data landscape.

In this short presentation, Big Data LDN Conference Chairman and Europe’s leading IT Industry Analyst in Data Management and Analytics, Mike Ferguson, will welcome everyone to Big Data LDN 2025. He will also summarise where companies are in data, analytics and AI in 2025, what the key challenges and trends are, how are these trends impacting on how companies build a data-driven enterprise and where you can find out more about these at the show.