This past year was one of technology’s most exciting with the emergence of generative AI, as leaders everywhere considered the possibilities it represented for their organisations.

While many have already recognised its value and are eager to continue innovating, others are inspired by its potential and are seeking ways to adopt it

To implement a successful AI analytics strategy, three key ingredients are essential: powerful AI models, clean data, and a data culture ready to leverage these solutions.

Join us as we examine the challenges and opportunities data leaders face in preparing their organisations for the AI era.

AI is as revolutionary to data as the computer was to the typewriter.

The hype of GenAI is unavoidable. In today’s AI-driven world, how can you enable and educate your organisation to embrace a GenAI strategy and narrow down your use cases to those that truly drive value?

Details to be confirmed soon

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.

In an era where data drives decision-making and innovation, data engineering stands at the forefront of technological advancement. 

This panel brings together leading experts; Chad Sanderson, Joe Reiss, Sarah Levy and Pushkar Garg to explore the critical challenges and opportunities shaping the field today.

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.

Meet some of the most prominent UK data founders and delve into what it takes to start a high-growth business in the data space. With the panel collective expertise covering SaaS, M&A, professional services, advisory, product companies and everything in between, this is an event not to miss. This panel is a true celebration of the UK entrepreneurial talent - you will learn about the founders’ personal journeys, their experience of significantly scaling and growing their businesses and the role that their tenacity, perseverance and determination to build something new and different have played in it. 

The panel will also be joined by a special panel guest Richard Shaw, who will share the investors outlook and the insight about the eco-system out there available to support new generation of data founders on their journey.

Featured panelists:

• Chris Tabb, co-founder and CCO, LEIT Data

• Anna Sutton, co-founder and CEO, Data Refinery, exited co-founder of Data Shed (acquired by Hippo Digital in 2023)

• Chelsea Wilkinson, co-founder and CEO, Data Diligence

• Rowena Humby, co-founder and CEO, Starcount

• Richard Shaw, Partner, Growth Capital Partners

• Guy Fighel, Venture Partner and Head of Data Program - Hetz Ventures

The panel will be hosted by Svetlana Tarnagurskaja, co-founder and CEO of The Dot Collective.

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 is transforming the world of work and creating new opportunities for individuals and organisations. However, to harness the power of data, one needs to develop the right skills and mindset. In this panel discussion, four experts from different sectors and backgrounds will share their insights and experiences on how to foster a culture of data-driven decision making and empower employees to use data effectively; how to identify and develop the technical, analytical, and soft skills that are essential for data professionals; how to address the talent gap and build a future-ready workforce that can leverage advanced analytics tools and techniques and how to leverage data skills to advance your career goals and create value for your organisation.

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! 

In today's data-centric business landscape, robust governance, comprehensive auditing, and resilient disaster recovery are paramount for ensuring data integrity, availability, and compliance. This session will explore best practices and advanced strategies for managing and securing your Power BI and Microsoft Fabric environments. Discover how to mitigate risks, optimize operational efficiency, and derive maximum value from your data assets.

Data is an open environment, and even the best code will break regularly due to upstream schema changes, flaky APIs, and poorly structured data. By embracing the reality of failure as a given, we can proactively architect our systems to minimize the impact of disruptions and ensure the continuity of our data operations. Attendees will learn practical techniques for anticipating specific failure modes and building resilient systems that can recover while minimizing the cost of problems.

Organizations are struggling with a lack of usage and low ROI for their BI practices. Users are overwhelmed with too much information, and they don’t know what they can trust. Attend this session to see how Metric Insights’ BI Portal works by integrating all your BI tools, reporting, and metrics into a single, consolidated catalog of governed BI assets that users can access, knowing it contains content they can trust.

Building visualizations in a BI tool is just the beginning. To create truly innovative data products, we must blend BI and data pipelines into a reactive, composable end-to-end system. Such a system adapts to changing business conditions, evolving technologies, and increased scale to meet customer needs. Join us to explore why “Analytics as Code” is the future of BI and learn how to make it a core component of your analytics engineering strategy.

This presentation will be delivered alongside a customer we have worked with for over 2 years. Austin Price CDO at PPL and I will present. This presentation explores how building a solid data platform foundation acts as a force multiplier, significantly accelerating your ability to deliver results. We'll delve into the importance of an architect-led data platform program delivered in an agile methodology based on a Business-aligned architecture runway. The Force Multiplier Effect Discover how a well-designed data platform can amplify your team's efficiency and reduce delivery friction. Architect-led Program We'll discuss the crucial role of an architect in providing the architecture runway for the data platform strategy and ensuring alignment with business needs. Agile Delivery Embrace the power of agile methodologies to build your data platform iteratively but aligned to the roadmap, focusing on delivering high-value features quickly and at scale Product & Feature Approach Learn how to break down your data platform development into manageable products and features, enabling faster iteration and adaptation. By using this approach you can build a data platform that empowers your organization to: Deliver insights and applications faster Reduce development time and costs Increase agility and adaptability How to create the force multiplier effect.

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.

Morrisons are driving business transformation with data, in part through near real-time ingestion of disparate datasets, which enable centralised critical actionable data within Google Cloud, but also operationally, by focussing on outcome driven data teams. Learn how being data driven is challenging, how data volume can be problematic, but also how the benefits of available live data enable success and aid future business growth.

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.