This session looks at the ever-increasing demand for data and AI, the current challenges slowing development and how companies can overcome these challenges and shorten time to value using generative AI and open tables like Apache Iceberg. It also looks at how this approach makes it possible to transitioning away from siloed analytical systems to a modern data architecture where multiple teams can create reusable data products across multiple clouds and op-premises environments using generative AI in Data Fabric and share that data across multiple analytical workloads. 

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

Simplify your GenAI journey and unlock the hidden power within your databases. Businesses often feel pressured to adopt new, specialized technologies to stay ahead. However, the power to revolutionize your applications with GenAI may already reside within your current database infrastructure. 

We’ll build understanding of vector capabilities, ease of use/ROI, and how PostgreSQL, enhanced with the pgvector extension, can address 80% of common GenAI use cases, providing a streamlined and cost-effective path to AI-driven solutions.

Join us to demystify the hype around dedicated vector databases and explore how built-in vector capabilities existing databases can efficiently support your GenAI workloads without extra overhead.

Elsevier is a leading provider of quality scientific data to the global research sector. We are all too aware that high-quality, well-structured data is the cornerstone of any data-driven product – particularly relevant as we are caught in the disruptive excitement of the Gen AI wave. We mustn’t lose sight of the role good data plays – garbage in garbage out is as applicable now as ever.

The generation and availability of high-quality data relies on good data governance and the adoption of FAIR (Findable, Accessible, Interoperable, Reusable) data principles, including ontologies. Our semantic technology stack and domain expertise helps drive this adoption. Structured data, such as ontology-tagged text and Knowledge Graphs can be the bedrock of explainable GenAI solutions such as we are seeing in the arena of scientific search.

As organizations transition from digital to AI-native, data becomes the linchpin of innovation, empowering AI to turn raw information into actionable insights. Cloudera hybrid data platform brings all data to modern use cases including Generative AI. This session explores how Cloudera can help your organization deploy robust AI use cases to production faster, without compromising performance, accuracy, and security.

In the world of GenAI, advancements are happening at a crazy speed. These advancements concern not only the algorithms but also the operations side of things. In this talk, we will go back to the basics, discuss the main principles of building robust ML systems (traceability, reproducibility, and monitoring), and explain what types of tools are required to support these principles for different types of applications.

How the development of GenAI affects representation and diversity Based on the work around moral usage of AI and wider themes of diversity and inclusion in data and SaaS companies, I'll be looking at current trends in the space and how to help establish better practice around representation.

The introduction of Generative AI in the enterprise heralds a new era of advanced analytics and operational efficiency. By harnessing the sophisticated capabilities of Gen AI, businesses can significantly accelerate their decision-making processes and empower their employees across multiple dimensions. Gen AI enables intricate data analysis, natural language processing, and decision-making with just a few prompts, facilitating faster innovation and competitive advantage.

However, implementation and optimization of Gen AI for enterprise analytics use cases present several challenges. Gen AI is hard to put into production, due to the complexities associated with data integration and secure data access. Additionally, enterprises struggle to tune and deliver consistently high quality and compelling responses to AI-driven questions.

Join this session to learn how implementing a data fabric can help accelerate time to value and enable Generative AI.

Crafting Tech Stacks to Embrace Traditional and Generative AI in Enterprise Environments In this talk, Bas will present a reference architecture for machine learning systems that incorporates MLOps standards and best practices. This blueprint promises scalability and effectiveness for ML platforms, integrating modern technological concepts such as feature stores, vector stores, and model registries seamlessly into the architecture. With a spotlight on emerging generative AI techniques like retrieval-augmented generation, attendees will gain valuable insights into harnessing the power of modern AI practices. Additionally, Bas will delve into the aspects of MLOps, including feedback loops and model monitoring, ensuring a holistic understanding of how to operationalize and optimize ML systems for sustained success.

We have a hypothesis, that 90% of people doing Gen AI today weren’t doing it two years ago. The landscape is full of people stumbling their way through it, from the AI academics learning that code for papers is not software development ready, all the way to data experts suddenly needing to learn a new skill.

In this talk, we'll go through what data engineers need to know to help get those AI projects off the ground. Starting with picking the right projects, execution plans, through to toolsets and skills that will make you shine.

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.

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.

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.

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.

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.

Join Nir Evron for an insightful session on the next wave of AI innovation. With Generative AI having revolutionized industries for nearly two years, we will explore emerging trends and ground breaking concepts that define the ‘Season 2 of AI’. Discover how these advancements are shaping the future of technology and driving unprecedented opportunities.

As the hype for AI grows, organizations are still wrestling with the fundamentals of data governance. The ambitions of executives and boardrooms to implement next-gen AI use cases hinges on a solid data foundation including cataloging, ownership, and data quality. Join Collibra’s Chief Data Citizen, Stijn Christiaens and Vodafone’s Sr. Data Governance Manager, Fede Frumento, to learn how Vodafone has used data governance fundamentals to increase the scalability and collaboration of GenAI use cases.

From a data perspective, an ideal scenario is one where practitioners can have a meaningful conversation with their data. In an era where data is both abundant and critical, the need for innovative methods to interact with and understand complex datasets has never been greater. Enter GraphRAG (Graph-based Retrieval-Augmented Generation), a cutting-edge approach that revolutionizes data interaction by seamlessly integrating graph theory with generative AI.

GraphRAG leverages the power of a knowledge graph to represent relationships within data, enabling more intuitive navigation and retrieval of relevant information. By augmenting these capabilities with state-of-the-art generation models, GraphRAG provides users with enriched, context-aware outputs that significantly surpass traditional query-response systems.

Attendees will gain insights into the underlying principles of GraphRAG, its architectural components, and practical applications across various domains, from healthcare to finance. We will demonstrate real-world use cases, showcasing how GraphRAG not only improves efficiency and accuracy in data handling but also democratizes access to complex insights, empowering users to reach their ideal state of conversing with their data. Join us to discover how GraphRAG is paving the way for the future of intelligent data interaction.

Many companies are under pressure to implement Gen AI ASAP, but not everyone sees the risks clearly. New Actian research shows nearly 80% of respondents think their data quality is up to the task. But real data prep takes more work than most business leaders think. How can you avoid the data prep pitfalls that can tank a Gen AI initiative? How can you move quickly—and confidently—into the Gen AI era? Actian’s SVP of Engineering & Product, Emma McGrattan and CMO Jennifer Jackson will share research and customer perspectives to explain true data readiness and how to optimize your Gen AI journey.

As data volumes multiply, business budgets shrink, and the data industry changes, relying on the old ways of executing can hold you and your team back. By embracing scalable, future-ready strategies, data engineers can shift focus to high-impact projects like AI and GenAI, helping your personal growth and your business stay ahead of the curve.

Join our session to:

• Learn how evolving your data architecture paves the way for AI and next-gen workloads

• Balance the trade-offs between building in-house and adopting modern tools for efficiency and scalability

• Discover how to transition to an AI-ready architecture, unlocking time for more innovative, revenue-generating projects.

While Generative AI has dominated technological discussions since the release of ChatGPT, it represents just a fraction of the broader AI landscape. Many organizations are still struggling to harness its potential. In this session, we’ll explore the key challenges that successful companies have overcome in their AI journeys and highlight the major opportunities for leveraging the full spectrum of data and AI technologies.

In this session, we'll explore how to translate all the latest data management trends: actionable data governance, generative AI, semantic ontologies, knowledge graphs, metadata management, into the business language and demonstrate the value of data initiatives quicker. For business users it's not just about keeping up with the latest tech trends. It's about the fundamental goals of lowering costs, increasing profitability and reducing time to value.