Organizations struggle to make sense of numerous programs and projects that overlap or operate in silos. This research will weave together data and analytics governance, MDM and data quality into one organized initiative that every CDAO should be interested in.

AI is moving faster than ever. AI techniques should bring adaptability to an uncertain world in constant flux. However, despite its extraordinary power and early promises, AI has not been leveraged to its full potential. What is missing? Where did we go wrong? Join us as we discuss our ambition for the future of AI and AI should do for us to deliver the value that we are expecting.

Small Language Models (SLMs) provide a viable alternative to Large Language Models (LLMs) for developing high-performing, cost-effective, and secure generative AI solutions. CDAOs, AI architects, and data architects should attend this presentation to gain insights into the strengths and weaknesses of SLMs and discover five specific use cases where SLMs outperform LLMs.

AI agents are emerging as an important trend since they enable levels of business adaptability, flexibility and agility that traditional AI systems can’t achieve. This flexibility is valuable in unpredictable environments where real-time monitoring and control aren’t practical. Autonomous behaviors, despite significant societal, legal and ethical implications, are the answer to the increasing complexity in our enterprise systems.

Data lakehouses continue to be hyped but do they replace or complement data lakes and data warehouses? Where do we stand from an architectural perspective? What is hype and what is real? What should be expected in the coming years?

Data fabric and data mesh are not mutually exclusive. Join us in this two-speaker debate session that aims to put an end to a five-year long debate comparing fabric and mesh. D&A leaders can deploy them independently, or best-case together. You will find out how you can deploy the fabric design to unify data management and mesh operating model to distribute data management.

Analytics is experiencing another monumental change. Just as visual drag and drop BI tools and augmented insights led to changes in analytics delivery, we now experience conversational interfaces, automated workflows and AI agents that cause us to rethink how analytics will be done. Join this session to learn the new technologies that are making an impact and how this will affect plans for future investment in analytics tools, platforms and solutions.

Although retrieval augmented generation is a very popular architectural pattern for delivering Q&A over complex internal information, it is also extremely hard to build a high quality, high accuracy RAG system. Come to this session to learn the 7 gotchas of RAG systems and best practices to improve their performance.

In a fragmented data landscape, reactive processes trap enterprise teams in firefighting mode, hindering innovation and scalability.Acceldata’s Agentic Data Management introduces a new paradigm, embedding proactive, AI-driven autonomy and cross-domain intelligence into data operations. By eliminating bottlenecks and reducing manual burden, it accelerates trustworthy insights and scalable governance. Join Acceldata to discover how forward-thinking enterprises are modernizing their data strategies to power innovation—and why autonomous operations are essential for thriving in an AI-first world.

As organizations scale GenAI from concept to production, they face challenges like ensuring accuracy, explaining responses, and connecting GenAI to unique knowledge. This session shows how GraphRAG combines knowledge graphs with retrieval-augmented generation to build GenAI apps grounded in enterprise data. Learn how companies like Klarna have deployed GenAI to build chatbots grounded in knowledge graphs, improving productivity and trust, while a major gaming company achieved 10x faster insights. We'll share real examples and practical steps for successful GenAI deployment.

Legacy systems slow organisations due to scale limits, risk, and cost. In this session, we will walkthrough how enterprises use Archon Data Store, our AI-powered archival platform, to create enterprise-wide data archival strategies for their legacy and modern data. Through use cases from finance, pharma and manufacturing - we will learn intelligent archival techniques that enable organisations to discover their data; align their past, present and future data footprint through decommissioning and migration while enhancing system performance, security and stewardship for their enterprise data.

This session will look at the quickly emerging domain of agentic AI. What are AI agents? What are the solutions and applications that will most benefit from an agent-based approach? What are the pitfalls to watch for when considering this fast-growing software engineering discipline? Join this session to know the answers to such questions and more.

Urgent Investments in data, analytics and AI use cases has put the spotlight once more on strong data management foundations. Is our Data even Ready for upcoming AI, analytics and data sharing initiatives is now top of mindshare for heads of data, CDAOs and their counterparts. Data Fabrics have emerged as a long term, foundational data management architecture that you should now pursue for sustained D&A success. This session will:
1. Help understand what data Fabrics are and what they mean for your data strategy and architecture
2. Help decide how to build and where to buy
3. Navigate the vendor landscape to assist in tech procurement decisions to aid your fabric journey

D&A value is not possible without data storytelling that offers a better way to engage communication findings than just BI reporting or data science notebooks. Join this session to know about the fundamentals of data storytelling and how to fill the gap between data science speakers and decision makers. It further discusses how to tell the best data storytelling and how to upscale data storytelling for future in landscape of GenAI.

Models have become a commodity and the true differentiator lies in your data. This session will showcase seven real case examples from Uber, Rechat, J.P. Morgan, ChatDOC, Arize AI, Qodo, and Unstructure that span the entire AI-delivery life cycle, demonstrating how to transform your data into AI-ready assets to unlock its full value.

Data catalogs suffer from a high failure rate that is often blamed on poor technology choices but are more often the result of nontechnical issues. This session will provide insight to data and analytics leaders in evaluating metadata management requirements, assessing readiness of organizations and best practices for getting started to implement a data catalog.

This workshop will guide participants through the process of defining their governing environment, architectures, and delivery models essential for executing strategy. This workshop discusses various models for CDAOs to consider, helping them plan potential shifts in their approach for the future.

You've likely encountered human resistance to your data and analytics governance initiative, which can be frustrating because what you are doing seems like common sense. The very people you think your governance initiative will help can derail or block it. This session explores the people challenges encountered, and lessons learned on the journey to governance failures and successes.

Securing and derisking AI requires new processes, tools and mindsets. Risks abound internally and externally while regulations take hold. This session outlines frameworks, tools and processes for managing AI trust, risk and security.

CDAOs and AI leaders often struggle to get started with GenAI. Attend this session to understand the first critical components you need to build or buy: Data, AI Engineering tools, a search and retrieval system, the application, and the right types of models. With these building blocks, you can build several working GenAI prototypes to help you prove the value and justify further investments.

This session will look at the quickly emerging domain of agentic AI. What are AI agents? What are the solutions and applications that will most benefit from an agent-based approach? What are the pitfalls to watch for when considering this fast-growing software engineering discipline? Join this session to know the answers to such questions and more.

Productivity and operational efficiency are one of the key measures of business performance and economics. GenAI has promising capabilities of improving productivity and operational efficiency of data management function, and data governance. Organizations should explore and assess those capabilities to align it with strategic goals to improve the productivity and operational efficiency.

This presentation provides a look at the multiple Hype Cycles that are pertinent to AI initiatives. This would include: Hype Cycle for AI, generative AI, data science and machine learning platforms, analytics and business intelligence, and possibly others.

Data architects are increasingly tasked with provisioning quality unstructured data to support AI models. However, little has been done to manage unstructured data beyond data security and privacy requirements. This session will look at what it takes to improve the quality of unstructured data and the emerging best practices in this space.

This session will share proven enterprise architecture best practices for augmenting Snowflake with data virtualization to deliver real-time insights. We'll explore how to address latency-sensitive use cases—such as month-end financial reconciliations—while ensuring data security and supporting cloud migration using Denodo. Attendees will learn how the combination of Snowflake and Denodo enables scalable, low-latency analytics across highly customized and distributed data environments.