Multi-Chapter | The Rise of the Data Project Manager
Modern organizations are investing heavily in data, analytics, and AI initiatives, yet many of these projects struggle to deliver lasting business value. Traditional project management approaches, which work well for predictable delivery, often fall short when applied to data work that is exploratory, iterative, and highly dependent on data quality and learning over time. This session explores why data projects behave differently from traditional initiatives and introduces the emerging role of the Data Project Manager as a practical response to these challenges. Rather than focusing on tools or technology, the discussion centers on how project managers can successfully lead data initiatives by managing uncertainty, aligning work to business outcomes, and owning the full lifecycle of data, from initial collection through long-term use. Drawing on real-world experience delivering data and technology projects across regulated industries, this session will examine common failure patterns in data projects, why downstream fixes often come too late, and how upstream involvement changes outcomes.
Attendees will learn how the Data Project Manager bridges the gap between business intent and technical execution, enabling teams to move from dashboards and models to sustained organizational value. This 60-minute session is designed for project managers, agile practitioners, and leaders who want to better understand how modern data initiatives fit within PMI-aligned ways of working. Participants will leave with a clearer perspective on how project management is evolving in the age of data, and how they can adapt their approach to lead these initiatives more effectively.
By the end of this session, participants will be able to:
- Explain why traditional project management approaches often struggle in data, analytics, and AI initiatives, particularly in environments characterized by uncertainty and experimentation.
- Identify the core responsibilities of the Data Project Manager and how this role bridges business objectives and technical execution across the full data lifecycle.
- Recognize common failure patterns in data projects and understand how early, upstream involvement improves delivery outcomes and long-term value.
- Apply PMI-aligned ways of working to modern data initiatives in order to better manage risk, stakeholder expectations, and evolving requirements.
Speakers
Photo Disclaimer
Upon participating in any PMI event, you are agreeing to allow PMI to use your likeness for use in its promotional material including their websites.
Postponement / Cancellation
Please refer to the Cancellation Policy section of the FAQ page
This event may be canceled or postponed by the Chapter, though all efforts will be made to avoid doing so. If canceled or postponed, notification will be made to all registrants via email.
