Our Programs
From foundational bootcamps to deep dives, we offer comprehensive training for every stage of your data stewardship journey.
Data Stewardship Foundations
Our flagship, hands-on program for leaders building data stewardship maturity. Learn to define purpose, design trust frameworks, and operationalize stewardship.

In-Person Intensive
Immersive experience with faculty and peers; includes field visits and a capstone sprint.
Hybrid Bootcamp
Flexible for distributed teams; combines live instruction and collaborative labs.
Online Bootcamp
Global cohort-based, fully remote with recordings and office hours.
LinkedIn Learning
Orientation and pre-work; ideal for team onboarding.
Deep Dives
Coming Soon: Focused one-hour masterclasses for experienced stewards who want to specialize in specific topics. Register your interest and join our wait list for the launch in the coming months.
The Data Stewards Canvas | Stewarding Strategic Data Futures
Ask the Right Questions | Defining Data Questions and Scoping Use Cases
Don't Overcollect | Defining the Minimum Viable Data Points
Stewarding The Data Lifecycle Approach | Step-by-Step Methodology
Beyond the Traditional | Non-Traditional and Synthetic Data
The Missing R in FAIR | Preparing AI-Ready Data towards FAIR-R Principles
Exchange
A vibrant network for practitioners, alumni, and partners to stay engaged and share knowledge.
Datathons
Collaborative sprints where teams tackle data governance challenges using real datasets.
Events & Salons
Keynotes, fireside chats, and panels with global thought leaders in data governance and stewardship.
Trends to Watch
Quarterly briefings on AI governance, data sovereignty, new legal standards, and cross-sector collaborations.
For Organizations
Tailored offerings to institutionalize data stewardship across your organization.
What Our Alumni Say
Join hundreds of data stewards who have transformed their organizations.
Recent News & Updates
2026-04-20T12:00:00
Data Stewardship Bootcamp Takes Off To Milan Lessons Learnt And An Engaged Community
The Data Tank in collaboration with Fondazione Cariplo, and as part of the Data Stewards Academy, completed, in the words of participants, a ‘unique’ one-month hybrid Data Stewardship Bootcamp in Milan. The bootcamp brought together and trained 23 participants from across civil society, social enterprises, and local and regional public and non-profit entities. Covering the entire Data Stewards Canvas via a step-by-step approach, the participants worked with several use-cases starting with identifying the demand for data and all the way to measuring impact for data-driven projects or services. The bootcamp combined lectures, including by affiliated guest faculty, with expert-led field visits to data driven institutions active in Milan. With three days in person in Milan and three online sessions, the bootcamp brought together local data and AI voices, but also managed to tap into global ones representing different contexts.
2026-04-09T12:00:00
Ai Summer Data Winter What The Ai Index Reveals And What It Doesnt Yet Measure
The AI Index Report 2026, released this week by Stanford HAI, offers a compelling portrait of what can only be described as an ongoing AI Summer. The indicators are striking: rapid adoption reaching more than half the population within three years, surging investment, near-human performance across multiple domains, and widespread deployment in science, medicine, and the economy. By nearly every conventional metric — capability, capital, and diffusion — AI is accelerating. Image copyrights: Picture by Deborah Lupton / https://betterimagesofai.org / https://creativecommons.org/licenses/by/4.0/
2026-04-07T12:00:00
Data Governance In The Ai Era 10 Shifts Redefining Data Institutions And Practice
As artificial intelligence systems rapidly evolve and start to impact nearly every sector of society, the conversation around governance has mainly focused on models (and their output): their transparency, fairness, accountability, and alignment. Yet this focus, while necessary, is incomplete. AI systems are only as reliable, equitable, and effective as the data (input) on which they are trained and operate.

