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.

To come up with new ideas and move beyond incremental improvement, we must start imagining at the third horizon and work our way back to the now. Join this session to know what Gartner's most provocative predictions are and what we can learn from them as D&A leaders.

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.

Data and analytics leaders and their data engineering teams are tasked with evaluating and selecting data integration tools. However, there are many options, which can be confusing. This session will explain the various types of data integration tools and technologies available in the market, and help you select the right data integration tool for your needs.

Responsible AI decisions are not black and white, they require trade-offs. Learn to make trade-offs and debate the alternatives to make AI governance and responsible AI decisions. Discuss controversial ideas in AI with your peers. Express your opinion and listen to what others are saying. Learn to ask the right questions and get the right answers to ensure responsible, trustworthy and ethical AI.

Generative AI continues to be a top priority for the C-suite and there has been an accelerated innovation in new AI models and products to enable it. In this session, IT leaders can learn about the key techniques and technologies powering one of the most transformative technology trends of this decade.

Organizations can face many challenges in operationalizing D&A and AI strategies. In this session, we discuss how to capitalize on value-based opportunities, engage with stakeholders and get to what matters.

As business leaders seek the adoption of AI-enabled capabilities across all aspects of operations, less than a third of D&A leaders express confidence that their organization is ready to meet the challenges associated with meeting AI-driven demand’. This multi-group discussion will cover:
Which components of the D&A value delivery chain are most in need of evolution?
What are the best next-generation D&A organizational & operating models suited for the AI-era?
What are the best KPIs for measuring ‘AI-readiness’ among systems, teams, and leaders?

CDAOs implement self-service analytics (SSA) to enable data-driven decision making across their organizations. However, SSA initiatives often fail to deliver on their full potential due to governance, trust, scalability and adoption challenges. This presentation provides a framework for CDAOs to balance control and agility within SSA to drive meaningful business value from data.

Asking your colleagues how analytics can help them often results in blank stares, defensiveness, or wildly incoherent suggestions involving AI. This session will show you how to work with your colleagues to pinpoint how you can help, identify the most helpful capabilities to build, and explain how to measure your impact.

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.

What is the role of CDAO? How can you assess if a particular job is a good fit for your aspirations? What common challenges do CDAOs face? What skills and traits are required to become a great CDAO? Whether a technologist aspiring to the role of CDAO, or a new CDAO not achieving the desired levels of traction, this session answers these questions and outlines three steps critical to laying a solid foundation for success.

This workshop will guide participants through the process of defining their governing environment, architectures, and delivery models that describe how strategy is executed. Types of models will be discussed for CDAOs to consider how they may want to shift their model in the future.

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

To position their teams as a must-have discipline that can fulfill cross-functional use cases, D&A leaders must optimize their organizational model. The optimal organizational model is one that balances enterprisewide capabilities focused on enablement with decentralized needs focused on outcomes. In this session you will learn the design principles behind the right D&A organizational model and how to balance a centralized team (focused on enablement) and decentralized needs (focused on outcomes).

Discuss with your peers the approaches, tips and pitfalls in communicating D&A strategy, approaches and value with executive leadership within the government. Understand how to communicate that the fast-changing world of D&A can be difficult, especially within areas of long-range planning and budgeting. Learn from your peers and build relationships in this session.

The enormous potential business value of AI is not going to materialize spontaneously. AI leaders should guide their organization toward an era in which AI is not only creating tangible business value but goes beyond to become a critical competitive differentiator and industry disruptor.

D&A is full of politics. What people say they want is often not what they really want with D&A. Resistance to becoming more data-driven is often left unspoken. This session will help you to recognize the most common political issues and the best practices to overcome them.

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 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.

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?

Chief data and analytics officers play a critical role in driving and overseeing major business changes to deliver enterprise value. Clear and actionable change-management plans are essential for both proactive and reactive data-driven change.

By following the steps discussed in this session, organizations can effectively assess their D&A governance platform requirements, ensuring they select a solution that address critical use cases, and overall business performance.

Top tech companies have utilized graphs to power everything, from fraud detection systems to recommendation engines, and they are now finding their way into use cases across industries. This session will introduce the concept of graph analytics and the algorithms used to find hidden insights in data that enhance decision making, with context as king. Additionally, we will explore how Knowledge Graphs can significantly augment LLMs, particularly in the context of Retrieval Augmented Generation (RAG) systems.

Gain valuable insights and practical advice on successfully piloting GenAI initiatives in public sector organizations. This interactive session allows you to ask a leading expert your most pressing questions and learn what your peers are doing.