Join us as we explore the challenges and learnings of implementing generative AI in real-world environments. This keynote presentation will delve into the key considerations for overcoming organisational blockers to support faster delivery cycles. 

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?

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 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.

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.

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.

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

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.

Overcome the limitations of your legacy data warehouse or BI systems and reap the benefits of a cloud-native stack with LeapLogic, Impetus’ automated cloud migration accelerator. Join our session to explore how LeapLogic’s end-to-end automated capabilities can fast-track and streamline the transformation of legacy data warehouse, ETL, Hadoop, analytics, and reporting workloads to the cloud. Gain actionable insights from real-world success stories of Fortune 500 enterprises that have successfully modernised their legacy workloads, positioning them at the forefront of the GenAI revolution. 

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!

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.

Generative AI (GenAI) has garnered significant attention for its potential to revolutionize various industries, from creative arts to data analysis. However, organizations are realizing that implementing GenAI is not as easy as just asking ChatGPT a few questions. Providing the most relevant and accurate contextual data to the LLM is critical if organizations are going to realize the full benefits of GenAI. Retrieval Augmented Generation, or RAG, is a well understood and effective technique for augmenting the original user prompt with additional, contextual data. However, many examples of RAG grossly oversimplify the reality of enterprise data ecosystems. In this session, we will examine how a Logical Data Fabric can make RAG a practical reality in large, complex organizations and deliver AI-ready data that make RAG effective and accurate.

"Are you ready to revolutionize how you handle data? Join us to discover how the Workspace

Group, a leading provider of flexible office spaces in London, transformed their data processes to create and enhance marketing materials more efficiently and cost effectively. As Workspace Group’s portfolio has expanded, they faced growing challenges in managing their property and unit information accurately and timely. To address these challenges, they have used FME to support data integration, automation, digitisation and standardisation. Recently, the combined power of FME and Generative AI have helped to transform the way digital assets are attributed and marketing materials are created. Learn how they have automated manual tasks to improve efficiency, freeing up time for their team to focus on more important projects. Join us to learn how FME can transform your data processes, connect diverse sources, and automate workflows. Don’t miss this chance to see how your organisation can achieve similar success and optimise your data workflows with AI and FME.

As many organizations strive to harness the transformative power of Generative AI, implementing a data fabric has emerged as the solution of choice to manage and leverage vast amounts of data effectively.

Join Kaycee Lai, Founder of Promethium, and Matt Clark, who leads data at National Grid Energy Transmission (NGET), as they explore how National Grid is deploying a data fabric to accelerate time-to-insight, enhance data value, and empower AI initiatives. They will discuss the specific challenges their team aimed to address, the strategic approach they took to implement the data fabric, and the critical role that data products play in delivering rapid analytics and enabling Generative AI.

Don’t miss this insightful session to learn how the company is pioneering data fabric technology to drive innovation and efficiency in the energy sector.

This presentation will explore the cutting-edge applications of generative AI within the highly regulated landscape of pharmaceuticals, highlighting the potential benefits for patient care while addressing the challenges of compliance and ethical standards. At the heart of this discussion lies Novo Nordisk's pioneering work in constructing a multi-modal clinical data platform designed for the secondary use of data. This platform is particularly crucial for the cultivation of high-quality datasets that are integral to the success of generative AI. The presentation will introduce the concept of AI agents - intelligent systems equipped with the capabilities of planning, utilizing tools, and accessing memory. Moreover, the session will highlight the crucial role AI agents play in bridging the data literacy gap among teams within the pharmaceutical sector. By facilitating a deeper understanding of data, these agents empower professionals across disciplines to collaborate more effectively and make strides towards transformative healthcare solutions. 

Attendees will gain valuable perspectives on how to responsibly harness the power of generative AI to accelerate clinical breakthroughs, ensuring that ethical considerations and regulatory requirements are met.

Are you struggling to gain leadership support, craving stakeholder engagement, and begging for proper funding? Even though you may create analytic Gen AI wonders with your data, it won’t matter unless you explain the value in practical business terms. Join The Data Whisperer’s rollicking and riotous review of current buzzwords and some practical tips to help you bridge the story gap between data and the business. n this session, you’ll learn:

• How to differentiate between a data management narrative and other data storytelling efforts 

• Strategies to secure executive sponsorship and ongoing funding 

• The 3Vs of Data Storytelling for effective Data Management

In this session we will discuss Gen AI and the issue we face in regards to cognitive biases. 

What are cognitive biases and how do they relate to Gen AI?

Personality traits for tech professionals in the world today, and how that has impacted the industry. 

How being an ‘other’ can be a USP and an advantage. 

We’ll look as diversity and how diversity drives innovation. 

We’ll take a look at Bootcamps and Apprenticeships in the UK, and how this can bring in more diversity without breaking the budget. 

Gen AI has been the sole talk of the town since last 18 months and leaders across the world are feeling the heat to leverage its benefit. However, is simply adding Gen AI to the work solving the problem or creating future Tech Debt. Can Gen AI supplement or (even) replace data professionals?

How do you build your data strategy around Gen AI with limited early experience and knowledge. Join this talk to find out.

Have you ever received 50 emails from an Executive asking why a number changed on a business reporting dashboard? Come and hear how Databricks customers are experimenting with Gen BI to explain “The Why”.

• IT and data teams build dashboards, the business continues to use Excel - the last-mile problem

• Our analytics tools don’t explain “The Why”

• GenAI allows us to blend context and semantics in a way we could never previously scale

We call this Generative BI, enabled by the Databricks Data Intelligence Platform.

To stay competitive in the current economy, businesses need to use data democratisation to gain insights through BI and analytics.

Breaking data silos, deriving 360° insights, blending data across business functions, and empowering everyone with insights can truly transform business outcomes.

Artificial intelligence is now augmenting every layer of business intelligence to be more powerful, democratising access to insights. By adopting a modern BI and analytics platform, businesses can unlock transformative potential and uncover growth opportunities.

Join us to start your BI journey and learn how AI is evolving in the data and analytics domain to meet emerging business needs.

Here's what you can expect from this session:

• The state of data and analytics adoption

• Data and analytics challenges faced by businesses

• How generative AI is reshaping analytical insights

• Guide to transforming outcomes by adopting a modern AI-driven BI platform

The quality and usability of data determine the success of data-driven projects, and it has never been more critical to establish an operational pipeline of high-quality data that is both secure and accessible. Once distinct disciplines, Data Governance, Master Data Management, and Generative AI have converged to deliver data that is insight- and AI-ready in record time. Join our experts for practical examples and actionable advice you can use to get started.

Most organizations are using GenAI in hopes of gaining easy access to information needed by their users to enable greater productivity. At the same time, it's also well-documented that LLMs can deliver inaccurate information. To be of value, users need to be able to trust that the answers presented to them are correct.

This is a key issue at the center of AI adoption and its applications in the real world. For example, many organizations are beginning to develop, test, and implement chatbots for internal and external use to provide answers to questions by using natural language. When those chatbots do not produce the right answers, all the time and effort put into creating them ends up wasted.

Join David Jayatillake, Cube's VP of AI, for an in-depth discussion on the current state of GenAI and the rise of the semantic layer.

In this talk, you will learn about:

The current state of GenAI

The rise of the semantic layer in modern data stack with AI

The significant differences between an AI chatbot with and without a semantic layer