In the rapidly evolving world of enterprise AI, traditional monolithic approaches are giving way to more agile and efficient architectures. This session will delve into how Multi-Agent Retrieval-Augmented Generation Systems (MARS) are transforming enterprise software development for AI applications. Learn about the core components of AI agents, the challenges of integrating LLMs with enterprise data, and how to build scalable, accurate, and high-performing AI applications

Combining cutting edge AI and anonymised hiring, ai.r Recruit is on a mission to level the playing field and help companies hire fairer and faster.

Why Attend? This session will equip you with the foresight and practical knowledge to integrate GenAI into your strategy successfully. You'll gain knowledge from real-world examples, helping you to embrace the next phase of AI development confidently.

• Look ahead to the future of Generative AI as we discuss emerging trends and new possibilities including autonomous agents and interactive AI. 

• We'll discuss how GenAI will continue to shape our world and what to expect in the coming years. 

• Get practical advice on how businesses can integrate GenAI into their operations, train their teams, and navigate data privacy and responsible AI.

• We'll share real-world success stories from industries like healthcare, finance, and entertainment, illustrating how GenAI is revolutionising these fields and making a significant impact on our daily lives.

In today's rapidly evolving digital landscape, companies must adapt their approach to Data Governance to remain competitive. With the proliferation of data and the increasing reliance on advanced technologies like AI and machine learning, to remain effective Data Governance needs to evolve and adapt.

Join Nicola as she shares key learnings for her Data Governance journey and how we have to adapt our approach to Data Governance to work with the evolving environment we operate in.

In a rapidly evolving landscape, the ability to pivot, reskill, and transition is not just advantageous—it's essential. 

This panel discussion, hosted by Uma Parekh - Senior Associate at Kubrick, will delve into the transformative power of career redirection and skills transference in the era of data-driven innovation. Uma, who transitioned from a successful career at a 'Big 4' consultancy to lead teams building next-generation technology, brings first-hand advice through telling her story. 

Joining Uma are representatives from Esure and the Metropolitan Police, organisations at the forefront of integrating data-centric strategies within their industries. 

Together, they will explore how organisations can effectively harness the potential of reskilling their existing workforce, the challenges for professionals transitioning into new domains, and the critical role that transferable skills and diverse experience play in driving innovation. 

This discussion will provide valuable insights for individuals and businesses alike, aiming to stay competitive and innovative as we move further into the world of AI. 

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.

Even as data teams remain lean in 2024, data engineers are still expected to swiftly deliver data for various use cases. Adding new data sources and updating existing ones consumes nearly half of a data engineer's time, hindering your organization's data and AI-led goals. Rivery's modern data platform solves this issue across all your data sources with an innovative blueprint and generative AI. Join this session to learn how to overcome unscalable data pipeline challenges and unlock the benefits of all of your Data.

The next big innovation in data management after separation of compute and storage is the open table formats. These formats have truly commoditized storage, allowing you to store data anywhere and run multiple compute workloads without vendor lock-in. This innovation addresses the biggest challenges of cloud data warehousing — performance, usability, and high costs—ushering in the era of the data lakehouse architecture.

In this session, discover how an AI-powered data lakehouse:

• Unlocks data for modern AI use cases

• Enhances performance and enables real-time analytics

• Reduces total cost of ownership (TCO) by up to 75%

• Delivers increased interoperability across the entire data landscape

Join us to explore how the integration of AI with the lakehouse architecture can transform your approach to data management and analytics.

In the past, a central data team handled data management. However, challenges arose with the rise of the modern data stack, leading to the demand for Data Mesh and data product management. Today, more organizations are attempting to enable self-service data management, but there’s no clear solution. This presentation will show how an analytical franchise model can help you manage data yourself with your current stack. It’ll also talk about what’s been done and how AI can make data management better in the future.

Join this session to discover how DataStax Astra DB can boost productivity, deploy GenAI apps in minutes, and transform customer experience. We’ll showcase an advanced semantic search use case on vectorising entire videos with specific timestamps and use natural language processing to find precise moments from the Olympics. Learn about the open-source model that runs locally, making this powerful tool both accessible and free. Additionally, explore hybrid search capabilities to integrate multiple videos into a single collection and streamline processes by only loading embeddings and metadata. Perfect for enhancing content management and delivering exceptional user experiences.

AI is changing our work and personal lives, offering unprecedented opportunities in almost every arena. However, many organizations risk undermining their AI-driven projects by neglecting the need to unify, protect, and improve their data from the outset. Join this session to see first-hand examples of how feeding different data sets into a custom Large Language Model (LLM) can impact outcomes and learn how to build your foundation of high-quality, fully governed data today.

In our data community, we tend to use a lot of technical jargon that is meaningless to business executives seeking outcome-oriented solutions. Instead of your business cases getting shuffled into technology budgets, bring your AI initiative to the forefront by focusing on business priorities and value. Data mesh, data fabric, data lakehouse projects and others have failed to do this, and have taken a toll on the rigor required to make your AI case. In this session you will learn to flip the script - talk value first, educate and provide data literacy to your executive team and stakeholders, and make your AI solutions a reality in record time, with the right level of investment.

For over three decades we have been powering people and businesses to think and behave differently. In this session, we will share our insights into how you can build the right data culture, by SEEing the value of data through three key pillars: Sponsorship, Education, and Embedding. Detail ? Data helps us to make better, more informed decisions ? and the role of data should not be considered as an ?add-on? to existing capabilities but something that underpins all of those capabilities. Organisations need to understand that this is not just an incremental, evolutionary shift that gives better access to data and richer visualisation ? but something truly transformative when a strong data culture is embedded, alongside elements such as predictive analytics and artificial intelligence. We will discuss with attendees: The importance of adopting a ?shift left? mindset to the use of data in understanding problems, and the designing, developing, testing and operating of solutions. The criticality of investing in culture, which has a disproportionately positive impact on the success of data transformation programmes. The success which can be achieved by following the SEEing model: ~ Sponsorship means demanding better data in order to make better decisions from the Board downwards, and equipping sponsors of business and change programmes to seek and know how to use the right data to deliver better outcomes. ~ Education means helping people understand the value that data can give them; driving demand for data and helping people to see that it should be a foundation in everything they do. ~ Embedding means making data experts integral to teams, in a similar way that DevOps brought operational staff into development teams, which helps to build up understanding and trust between data experts and data users/beneficiaries, increasing domain knowledge in data experts and data/analytics knowledge in the rest of the team. The session will conclude with Q+A.

Join Scott Gamester as he challenges the outdated promises of legacy BI and self-service analytics tools. This session will explore the key issues that have hindered true data-driven decision-making and how modern solutions like Sigma Computing, Databricks, and Snowflake are redefining the landscape. Scott will demonstrate how integrating these platforms empowers business analysts, driving innovation at the edge and enabling AI-enhanced insights. Attendees will learn how these advancements are transforming business empowerment and fostering a new era of creativity and efficiency in analytics.

Everyone wants to take advantage of AI but to truly do so, the data must be made ready for use. Every data team has been asked to make their data ready for use by AI. But what does that actually look like in practice? How do you know if you're there? And how do you get there if you're not? This session will explore how AI is changing data management, share best practices when using AI for data management, and provide a glimpse into the future of how data consumption might look in 5 years.

Your world is filled with an ever-changing landscape of tools that create and use metadata. Each tool is useful, but independent, unable to share and link what it knows to information from other tools. The result is a disconnected story throughout your data and AI operations, making it hard to know where data came from, how it can and should be processed; leading to uncertainty in the trustworthiness of your AI results.

Using open source software from the Linux Foundation, (including Egeria, Open Lineage, Unity Catalog) we will share a simple approach to incrementally link and govern these tools to create end-to-end lineage, provenance and information sharing along your tool chains.

Discover how a leading optics & photonics manufacturer is revolutionising its technical support by implementing an AI chatbot, resulting in significantly reduced response times and improved accuracy, ultimately enhancing customer satisfaction and operational efficiency.

Imagine what's possible with social media analytics in a world of Generative AI: a whole new level of depth, speed and accuracy in understanding how your customers shop, how they work, how they live, and how they feel about key topics.

In this session, you’ll learn how to capture the context shaping your customers’ environment, emotions and behaviour, and to operationalize this across the enterprise for competitive advantage. Join Quid Founder and President Bob Goodson to discover how the biggest brands in the world are pioneering this new approach.

Discover key insights into Aviva's ongoing journey of integrating data and AI more deeply into their business operations. This session will highlight the value created by their technical teams, address current challenges and business priorities, and outline the roadmap for enabling the democratization of data and AI within the organization. Attendees will gain practical knowledge and actionable strategies to apply in their own data and AI initiatives.

From its founding in 2023, Skyscanner has leveraged analytical data to optimise business and traveler experiences. And with more than 110 million monthly users resulting in 30+ billion analytical data events per day, Skyscanner is an expert at managing data at scale.

Join Michael Ewins, Director of Engineering at Skyscanner, to learn how his team develops and executes data strategies centered on their core principles of data reliability, trust and rapid data-driven decision making. Michael will dive into the challenges his team faces navigating complex lineage, strategies for effectively combating data incidents, how they simplified their analytics infrastructure for a more practical approach to data governance, and their success in implementing impactful ML and AI business-critical use cases.

Big data means big implications in terms of the cost of infrastructure and the complexity of running in production. LiveEO sells a data product based on Satellite imagery—a dataset that’s notoriously huge. Because this product is used in critical conditions such as disaster response and supply chain compliance, efficiency is key for the product to be successful.

Every data request has serious cost implications, from fetching the raw image from space to actually processing it on thousands of GPUs. To maximize their first-run success rate and therefore efficiency, LiveEO built a composable data platform to minimize failure, expose new data products faster to dependent teams, and scale efficiently.

In today’s data-driven world, organizations are increasingly challenged to extract meaningful insights from both structured and unstructured data. Join Matillion and Snowflake in this exclusive session where we explore the transformative power of generative AI within data pipelines, leveraging Snowflake's robust platform and Cortex's advanced capabilities.

This session will guide you through practical use cases that demonstrate how to integrate unstructured and structured data to unlock new insights seamlessly:

Transforming Unstructured Data into Actionable Intelligence:

Discover how to convert customer reviews into structured data by labeling actionable items, extracting product names, and assessing sentiment. We’ll walk you through creating a BI dashboard and generating reports that highlight actionable defects and desired features, empowering your team to make data-driven decisions.

Generating Executive Summaries from Structured Data:

Learn how to generate insightful commentary from your existing structured data. We’ll show you how to create concise executive summaries and trend analyses, integrating contextual information such as competitor activities or regional updates. Imagine automating a weekly Slack message to your leadership team, complete with key sales trends and strategic insights.

Throughout this session, we will showcase the capabilities of Cortex, demonstrating how it can be seamlessly integrated into your data pipelines to enhance your data processing workflows. Whether you’re looking to improve customer experience, drive operational efficiency, or stay ahead of the competition, this session will provide you with the tools and techniques to harness the full potential of your data.

Join us to learn how to turn data into actionable insights that drive business success.

During his talk, Alex will discuss the value of moving from a batch-based architecture to a real-time, event-driven architecture with Apache Kafka®. He will then explain how you can build valuable data products with Confluent that unlock high-volume performance, data governance, and AI use cases.