The success of AI initiatives hinges on DATA. According to recent research, only 10% of enterprises will achieve the expected ROI from their Generative AI deployments, with data quality issues being the most cited reason for failure. The core message is clear: 'You are as AI-ready as your data.' This session will explore practical approaches to overcoming common data challenges and ensuring your data meets the specific requirements of AI techniques.

Key Takeaways:

• Understanding AI Readiness & how to assess it?

• AI-Ready Data: Two core Foundations

• Build a scalable data infrastructure that accelerates AI deployment and innovation. DQLabs Framework & Practical Approaches to fix your data problems.

Why Attend? You'll walk away with a comprehensive understanding of various GenAI models, their practical applications, and the strategies to harness their full potential responsibly.

• Discover the functionality of key GenAI models, including GPT, Gemini, and Open-source alternatives. 

• Learn how AI assistants, business process automation, co-pilots, and autonomous agents can work for your business. 

• Understand what each model excels at and where improvements are needed. We’ll provide a clear, comparative analysis to help you understand their capabilities and limitations. 

• Learn how we can ensure we are following responsible AI principles

• Explore the services and techniques that enhance the capability of GenAI. 

• Learn how to get AI to work for you and identify the skills your workforce needs going forward to excel in the era of AI.

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.

Looking to deliver safe, scalable, cost-effective, and future-proof LLM applications aligned with your operations and governance principles? Enter: The LLM Mesh. In this session, we’ll explore how Dataiku equips IT and Data teams to build secure, enterprise-ready GenAI applications, ensuring maximum control while delivering the high performance your business demands.

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.

There are many things to think about on your Generative AI journey, but in this talk we’ll focus on two key ones. Have you identified use cases that will solve real business problems? Secondly, is your data platform prepared? 

From this session, Cynozure’s Solution Architect, Tom Wilson will share his experience of what it takes to successfully integrate GenAI across your data platform, touching on data quality, governance and model management. With this, he’ll also share the practical applications of GenAI, both now and the near-future, that will positively shake up the way we do business and deliver value to organisations that embrace them.  

Join us to learn about: 

• The important role your data platform plays in unlocking GenAI’s potential 

• Lessons, experiences and watch-outs from doing this 

• Use cases GenAI is best suited to right now 

• The complex and evolved use cases we can expect to see going forward  

Now that the hype of Gen AI is slowing down, the data functions are expected to scale effectively and realise the value from a technology that is evolving even faster than it can be implemented. So how do data leaders ensure that the benefits are optimised, the risks reduced and that the reality is not overtaken by the hype?  

Beyond deployment and value creation, there is the issue of trust-in the tools, the data and the outputs. To say nothing of the fear of people that their roles will be replaced! What are the skills that the ‘new’ data leader needs to perfect to manage teams, stakeholders and growing expectations?  

Hear from the lived experience from 2 of the industry’s leading proponents as they discuss their journeys and share their knowledge.

How about a workplace where generative AI accelerates every data management task, transforming routine into innovative experiences? A vision which can be in production for the AWS customers in just 60 days through a combination of Amazon Bedrock, which enables rapid development and deployment of AI applications, and Stratio Generative AI Data Fabric, which provides accurate output based on quality data with business meaning. Join us to learn how a combination of these products is empowering data managers and chief data officers to drive innovation and efficiency across their organizations. 

As generative AI ramps up, there is a new urgency for database and analytics modernisation as the most popular and impactful AI innovations can be found in the cloud. Learn how to build a modern, cloud-based data foundation for data-driven applications, real-time analytics, and high-performance, immersive gen AI experiences.

As Generative AI continues to revolutionize industries, having high-quality, well-prepared data has never been more crucial. In this session, Emma McGrattan, SVP of Engineering & Product at Actian, and Guillaume Bodet, CPTO at Zeenea, will explore how Zeenea's cutting-edge Data Discovery Platform, now part of Actian, is poised to play a pivotal role in achieving data readiness for GenAI. Attendees will discover how Zeenea’s metadata management solutions, including its comprehensive data catalog, lineage insights, quality index, business glossary, and data marketplace, empower organizations to truly know and trust their data. Join us to learn how to leverage these tools to mitigate risks, ensure compliance, and confidently unlock the full potential of GenAI in your organization. Don’t miss this opportunity to prepare your data for the next wave of AI innovation! Speaker Bios: Emma McGrattan, SVP of Engineering & Product, Actian Emma is SVP of Engineering and Product at Actian leading global research and development. She is a recognized authority in data management and analytics technologies and holds multiple patents. Emma has over two decades of experience leading a global software development organization focused on innovation in high-performance analytics, data management, integration, and application development technologies. Prior to joining Actian, Emma was Vice President for Ingres at Computer Associates. Educated in Ireland, Emma holds a Bachelor of Electrical Engineering degree from Dublin City University.

As organisations shift from generative AI proof of concepts to building production ready applications, the requirements for efficiency, monitoring, safety and governance become critical to both trust and success.

You will learn:

Key design patterns and methodology for evaluating, experimenting and monitoring enterprise gen AI apps to address common failure modes

The role of iteration and improvement as part of ongoing delivery

Practical considerations for implementation using examples from Snowflake’s Cortex Analyst, Cortex Search and TruLens, an open source project.