6:00 pm - Intro & Drinks hosted by Chris Tabb

6:10 pm - Session One - High Performance Data Products

David Richardson, Jon Cooke, Taylor McGrath, Mark van der Heijden

6:30pm - Session Two - High Performance Data Models

Joe Reis 🤓, Keith Belanger, Nick White, Eevamaija Virtanen

6:50pm - Pizza and Drinks 🍕🥤🍷🍻

7:00pm - Session Three - High Performance AI

Alex Chung, Jai Parmar, Sonny Rivera, Addie McNamara

7:20pm - Town Hall Debate

Sponsors: Coalesce, LEIT DATA, Rivery, SqlDBM, ThoughtSpot 

Establishing a solid data foundation within your organisation is a crucial element for AI initiatives. Having this foundation enables your organisation to align its data strategies with your overall business strategies, to help maximise the return on your AI and data investments.

Join our session to explore how "data is the fuel for AI" and how you can unlock the potential of your AI efforts, drive innovation and achieve a sustainable competitive advantage.

The data engineer role has expanded far beyond data pipeline management. Data engineers are now tasked with managing scalable infrastructure, optimizing cloud resources, and ensuring real-time data processing, while keeping costs in check - which continues to be quite challenging.

In this session, Revefi will demonstrate Raden, the world’s first AI data engineer. Raden augments data teams with “distinguished engineer level” expertise in data architecture, system performance, optimization, and cost management.

Raden uses GenAI and AI to address these challenges by working with your team as an 👩‍✈️ AutoPilot and/or 👨‍✈️ CoPilot by automating critical functions such as Data Quality, Data Observability, Spend Management, Performance Management, and Usage Management, allowing your data team to tackle complex use cases with ease.

Join us to discover how you can revamp your data engineering practices and dramatically improve the ROI from your data investments 

In today’s modern Data & AI world, it’s easy to fall into one of a number of camps with regards to governance. Those in the data world may tell you it’s all about governing your data to ensure success, while those working with modern AI may say to achieve real success with your AI applications, governance of your AI models should be the focus above everything else. 

BUT to the truly enlightened, it’s clear that there are 2 real steps to ensuring successful, trustworthy and reliable outcomes, no matter what you hope to achieve with your data & AI . 

Join Ian & Rob as they show you how you can quickly and easily deliver complete governance of both your data and AI and in doing so deliver both trustworthy outcomes and the maximum value & to your business.

In this flagship Big Data LDN keynote debate, 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 impact of Generative AI, the implications of key industry trends, how best to deal with real-world customer challenges, how to build a modern data and analytics (D&A) architecture, how to manage, produce, share and govern data and AI, 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-driven enterprise from seasoned executives and an experienced industry analyst in a packed, unscripted, candid discussion.

In today’s fast-evolving big data landscape, having a solid data strategy is crucial. Our session will explore how leaders develop and execute data strategies, and whether these strategies are still essential in 2024. We will cover the key elements of a successful data strategy, the necessity of adapting to technological advancements like AI and evolving data privacy regulations, and provide insights from industry leaders who have effectively navigated these changes. We'll discuss the future trajectory of data strategies, questioning if traditional approaches still hold value or if new paradigms are emerging. This session is perfect for technology leaders, data professionals, and anyone keen on harnessing data for business success.

Data practitioners are feeling pressure around the realities and real-life considerations of building out a data stack that can handle the next generation of data problems in addition to today's data challenges. Considerations like minimizing complexity and cost while focusing on scalability and performance are at the forefront of the data world right now, and how this works in a world where LLMs and deep learning are becoming table stakes is paramount. There are questions about data management at this scale, as well as how to fold in legacy infrastructure and architectures. We'll discuss the modern AI data stack in this talk, delving into the realities of building the data ecosystem of the future.

Artificial Intelligence has transitioned from a niche concept to a widespread force shaping the business world's landscape. Streaming and AI integration have emerged as crucial drivers in this digital transformation era, focusing on the dynamic and real-time facets of data flow to generate contextually relevant predictions.

Businesses across diverse sectors increasingly adopt AI technology to optimise operations, stay competitive, and augment user experiences. However, AI's true potential only unfolds when applied to the right data sets, at the right moment, and within the appropriate context. In this session, Italo will discuss how AI and Streaming can work together to provide the latest and freshest data, be it about our customers, your business, or the market to your business.

Join us as we unlock the secrets of data-driven strategies that drive profit, loyalty, and hyper-personalised experiences, with Capgemini and a Women in Data leadership panel.

At this year’s Big Data London, Women in Data & Capgemini are back with another must-see panel, featuring a diverse and engaging group of female data leaders and their allies from across the Retail & CPG worlds. Last year’s session was one of the most oversubscribed events of the day, with standing room only, thanks to its thought-provoking and honest discussions. This year’s panel promises the same dynamic as they tackle the conundrum of balancing margin focus with rewarding customer loyalty and how data plays a key role. 

The panellists, as well as sharing their own career journeys and experience, will explore how they’ve approached bold strategies that move beyond immediate profits to emphasise the long-term value of customer data and loyalty. They’ll explore how data, analytics & ai can uncover deep insights into customer behaviours and preferences, enabling brands to create personalised experiences and loyalty programs that boost engagement and build lasting trust. 

The discussion will highlight the importance of seeing customer data as a strategic asset. By investing in data collection and analysis, companies can identify trends, predict future behaviours, and tailor their offerings to meet evolving customer needs. This approach can drive repeat business and increase customer lifetime value, ultimately leading to higher margins over time. 

This year’s panel will explore the how data and boldness are key for a balanced strategy that blends margin management with a robust focus on customer loyalty. Using data smartly is key to achieving sustainable profit growth and strengthening brand loyalty. Don’t miss out on what promises to be an inspiring and insightful discussion! 

Our panel discussion explores the transformative potential of big data and AI across diverse industries. We will address key technical challenges such as data management and model scalability, along with ethical and privacy concerns, including data utilization and algorithmic biases. Looking ahead, we will discuss future trends and emerging AI breakthroughs. Emphasizing interdisciplinary collaboration, we advocate for diverse teams to ensure fairness and innovation in AI solutions. This dialogue aims to illuminate the complexities and opportunities in big data and AI.

In this presentation, we will explore the transformative potential of Generative AI, a rapidly evolving field poised to redefine industries across the globe. We will begin by examining the market potential and addressing key challenges surrounding GenAI adoption, providing a comprehensive overview of its current landscape. Following this, we will delve into SAS's innovative approach to GenAI, highlighting our cutting-edge capabilities that empower organisations to harness its full potential. Finally, we will share real-world applications where SAS has successfully enabled organisations to implement GenAI solutions, driving tangible business value and innovation. Join us to gain valuable insights into the future of GenAI and learn how SAS is at the forefront of this technological revolution.

The massive interest in AI solutions has sparked a huge and pervasive wave of AI projects. We are now entering a second phase where the AI projects that have proven value are looking for operational landing places in enterprise environments. This is visible through the big hype for AI data systems like vector databases and feature stores. This phase of AI operationalizing is the hour of databases, which have proven already to be the battle-proof bedrock for data management enterprise environments. 

Postgres is naturally a front runner in this space. AI workloads are entirely tied to data, they start with data, they run on data and they produce data. Join this talk for a walkthrough on popular AI application flows, their strong ties to data and Postgres' strong operational qualities and demonstrate how they form the perfect environment for mission critical AI solutions in an enterprise.

AI is full of buzzwords, but what do they really mean for your business? In this 30-minute session, we’ll demystify key AI terms such as Artificial Intelligence, Machine Learning, Deep Learning, NLP, and MLOps. More importantly, we’ll demonstrate how these concepts can be applied to deliver tangible business value.

Through practical case studies, you’ll discover how organisations are using AI to optimise processes and achieve measurable outcomes. We’ll also discuss how to align AI initiatives with your business objectives to ensure success.

Join us for an insightful journey that simplifies AI and equips you with actionable strategies. Plus, stay for an interactive Q&A to explore how these ideas can be tailored to your needs.

Note: Visit Billigence at Stand Y239 for further insights.

Everything has changed in the last year with Generative AI entering onto the scene. This means a re-shuffling of priorities and budgets, putting AI-enabled Data & Analytics right back at the top of the agenda. In this session we will discuss: 

• That there is no Generative AI without data – but it has to be the right data 

• The importance of being able to bring together organised and trusted data 

• Why your data integration strategy is the foundation to successfully using AI

Discover how D&G's diverse leadership has unified our data team by leveraging advanced tools and AI technologies. Learn how we foster a collaborative culture that drives innovation and impactful outcomes through state-of-the-art strategic analytics and AI-driven insights. Join us to explore strategies for integrating cutting-edge tech with diverse perspectives to enhance team performance and achieve impactful business and customer outcomes. 

As data continues to grow in complexity, the need for a unified data layer with rich semantic business meaning has become more critical than ever. This session examines the transformative impact of integrating generative AI with a well-structured, unified data layer, emphasizing how this combination unlocks new levels of intelligence and efficiency. By standardizing and contextualizing data across the organization, companies can fully leverage the power of generative AI to drive insights, automation, and decision-making. Explore practical strategies and case studies that highlight how a unified data layer is the key to harnessing generative AI, marking the moment when data management truly evolved. Don’t miss this opportunity to learn how to prepare your data infrastructure for the future.

Join us at the Gen AI theater for an exclusive fireside chat with Matthew Thomson, Nokia’s head of data and digital, and Marianne Taudiere, Quid’s vice president of EMEA. Delve into how predictive analytics is revolutionizing strategic functions, explore the pivotal role of data in Nokia’s operations, and discover compelling case studies showcasing the transformative impact of Generative AI. Don’t miss this engaging session to learn how Gen AI is shaping the future of business!

Improve your data infrastructure with governance and security, using proven methods and best practices. Break down data silos, foster collaboration, and optimise data accessibility, empowering your business units with the data and technologies they need. Learn how AI improves efficiency and streamlines data product development. And see how Microsoft Fabric simplifies data estate modernization with a focus on unifying your data in an open and governed foundation.

PrimaryBid, a UK-based technology business which connects retail investors to capital market transactions, is no stranger to working within a highly regulated, complex industry. As the team prepares for a global expansion beyond Europe and into the US and Middle East, they're planning for even higher stakes as they increase the scale of their operations and external data products.

Hear from PrimaryBid's Director of Data & AI, Andy Turner, as he shares PrimaryBid's data journey, including how they rebuilt their data stack from the ground up to ensure accurate, reliable data across global markets, the value (and challenges) of delivering external data products, and how data observability has played a crucial role throughout PrimaryBid's expansion.

In today’s data-driven world, whether you’re building your own data pipelines or relying on third-party vendors, understanding the fundamentals of great data movement systems is invaluable. It’s not just about making things work—it’s about ensuring your data operations are reliable, scalable, and cost-effective.

As an early employee and Airbyte’s Platform Architect, I’ve spent the last 3.5 years working through the challenges and intricacies of building a data movement platform. Along the way, I’ve learned some important lessons, often the hard way, that I believe could be helpful to others who are on a similar journey.

In this session, I’ll share these lessons in the hope that my experiences can offer some guidance, whether you’re just starting out or looking to refine what you’ve already built. I’ll also touch on how the rapid rise of generative AI is changing the landscape, and how we’re trying to adapt to these new challenges. My goal is to provide insights anyone can take back to their own projects, helping them avoid some of the pitfalls and navigate the complexities of modern data movement.

2 - 3 Main Actionable Takeaways:

• A general framework for designing a data movement system.

• Crucial fine print such as managing various destination memory types, the surprising need to re-import data and the shortcuts & pitfalls of artificial cursors.

• Adjusting data movement systems for an AI-first world.

Exploring the practical applications of generative AI in driving data-driven decision-making within our organisations. From simplifying marketing optimisation decisions to decentralising insights, this talk showcases how businesses leverage generative AI to innovate and adapt in today's dynamic landscape. So, join us to discover how this cutting-edge technology is revolutionising decision-making, driving growth, and providing a competitive edge in our business.

We are in an era of heavy learning when it comes to delivering successful AI implementations across our organizations. In fact, the best AI use cases and outcomes are around the corner and still to come. However, there are significant takeaways from first projects all around us that can guide, accelerate, and improve our own journeys. There are also key differences and considerations in how IT teams deploy AI projects and technologies. Attend this session to learn the four key data-centric must haves to increase AI initiative success based on current Quest and Sparkle client experiences from around the world and use them as a catalyst to effectively trailblaze your own efforts.

For decades, data modeling has been fragmented by use cases: applications, analytics, and machine learning/AI. This leads to data siloing and “throwing data over the wall.”

With the emergence of AI, streaming data, and “shifting left" are changing data modeling, these siloed approaches are insufficient for the diverse world of data use cases. Today's practitioners must possess an end-to-end understanding of the myriad techniques for modeling data throughout the data lifecycle. This presentation covers "mixed model arts," which advocates converging various data modeling methods and the innovations of new ones.

Prioritizing Product Roadmaps with Causal Inference Methods. In the talk, I'll be walking through an example of turning an ambiguous ask into insights that lead to an action plan for what to build in the coming year. Using Double ML on our workout data allowed us to tackle the tricky question of causality in a product landscape where we haven't tested many features.