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).
talk-data.com
Speaker
Michael Gabbard
3
talks
Michael Gabbard is Senior Director Analyst within the data and analytics leadership and value research team. He specializes in supporting global data and analytics leaders (D&A), CIOs, COOs and other top executives achieve success with data-driven transformation. Michael's expertise includes data-driven business transformation, D&A strategy development, operating model design, best practices in operational excellence, D&A organizational design, and D&A cloud cost management, optimization and FinOps. He also leads the data and analytics strategy and operating model (DASOM) research as well as the annual state of data analytics leader and CDAO survey. He has 15 years experience in consulting, best practices development, executive advisory and research.
Bio from: gartner-data-analytics-india-2025
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Cloud has exposed the cost of individual workloads at a highly granular level. It is, in essence, a complex cost optimization problem. This session provides the tools for D&A leaders to understand how to manage and evolve cloud-operating models. We provide the foundations in the three rings of financial governance, and explore the state and future of FinOps.
D&A leaders and teams are at an AI-driven inflection point. They are crucial to enable business value through AI-readiness but must evolve their strategy and operating model to meet their organization’s AI ambitions. Reporting from the Gartner 2025 CDAO Agenda Survey, this session reveals actions successful D&A leaders have taken to deliver business outcomes from AI, data, and analytics, and what they need to do next year.