CDAO Dallas 2025 schedule

• Examine the current maturity of your data analytics capabilities
• Articulate the end goal of a data-driven organization
• How to implement the transformation roadmap with actionable phases?

• How to support the transition from decision support (charts and graphs) to decision automation (models)
• Managing accountability for the Amplified Value and Amplified Risk of AI
• Scaling AI despite unprecedented operational complexity
• How to embrace the CDO/CDAO responsibility as the enterprise AI leader?

• How can data governance create a collaborative environment where data professionals with diverse skill sets (technical, analytical, communication) can work together effectively to address challenges and opportunities?
• What approaches or best practices have you found effective in balancing regulatory requirements while promoting innovation within your data team?
• What strategies can the panel recommend for fostering a culture of data sharing and breaking down silos that may exist between different teams within the organization?
• How can organizations measure the effectiveness of their data governance program?

Moderated by:

Lauren Morandi Inskeep, VP, Data Governance, Chief Data Office, T. ROWE PRICE

Panelists:

David Morley, Former Director of Reporting and Data Governance, U.S. DEPARTMENT OF THE TREASURY

CDAOs are under increased pressure to deliver business value and show an ROI from data and analytics investments. This CDAO panel discussion will explore:

• The importance of building strong and trusted business sponsorship
• Why creating a data culture is a foundational requirement
• Communicating and selling your ideas to business leaders
• Starting small to provide business value

Moderated by:

Erum Manzoor, SVP, CITI

Panelists:

Benjamin Newcome, VP, Payments Data & Analytics, JPMORGAN CHASE

Panelists:

Jasper Cannon, Strategy Consultant, CANNON STRATEGY CONSULTING

• How to build trust in the data and deliver value 
• Avoiding paralysis by analysis 
• Becoming more hypothesis minded and understanding the "why" 

Enterprises are increasingly adopting AI applications and utilizing various types of data (structured, unstructured, and semi-structured) to enhance their business processes across different industries. However, despite recognizing the significance and potential of AI, organizations often face challenges in formulating a strategy and implementing it effectively. To fully capitalize on the benefits of AI, enterprises need to integrate AI at the data level, ensuring that it supports the entire data management lifecycle, from data ingestion to curation and discovery. This integration will enable the development of applications that are built on top of the data, maximizing the potential of AI.

• What are the best methods for ensuring data is understood up and down your enterprise, and how best to articulate the value of relevant projects to senior leadership?
• Aligning data analytics & AI projects with business goals
• Customizing communication for different leadership levels

• Leveraging AI to enhance SAP data integration and drive performance 
• Fostering a data-centric approach across all levels of the organization 
• Maximizing ROI and unlocking the potential of data in digital transformation 

Moderated by:

James Bruckschen, Sales Engineer & Tech Evangelist, ONIBEX

Contribuitors:

Gustavo Estrada, CEO, ONIBEX

Moderated by:

Jose Valladares, Principal Solution Advisor, SAP