This program is built for the cross-functional leadership teams that set data policy, govern data access, and answer for outcomes when something goes wrong. A typical engagement is sponsored by a learning or talent leader and convenes the people who must govern data together: the chief data or analytics officer and their data owners, technology and platform leaders, risk officers, compliance and privacy leaders, general counsel, and the business executives who productize data. Because examples are drawn from financial services, healthcare, retail, and the public sector, participants map each principle onto their own regulatory and operational reality. It is designed to be brought as a cohort, so the functions that must align on data and AI governance build a shared language and a common standard together. No technical background is required — the program assumes decision-making authority and the judgment that comes with it, not the ability to read code.
Is this an open-enrollment course or a custom program?
It is a custom program your organization brings to its teams. We tailor the content, depth, format, and schedule to your organization and deliver it to your cohort privately, rather than as a public course.
How do you customize the program for our organization?
We start from your data challenges and objectives, then tailor the program to your data estate, regulatory profile, and AI use cases. The standard seven-session, one-day design is the baseline — it can be deepened, resequenced, or mapped to your own environment so the working scenario reflects your organization and industry.
What is data governance, and why does it matter now?
Data governance is the system of policies, standards, roles, and controls that determines who is accountable for data and whether an organization can trust it. It matters now because data products have become first-class assets, regulators have expanded their reach, and AI systems inherit every weakness in the data beneath them — so governance has moved from a back-office function to an executive one.
How do we implement data governance across our organization?
By building a shared standard the relevant functions apply together. The program moves a cross-functional cohort — data, technology, risk, compliance, legal, and business — through an end-to-end governance program, from maturity assessment to a board-ready strategy, so the people who must govern data leave with the same language, the same operating model, and a 12-month roadmap they can apply to every future initiative.
How is this different from a technical data-management course?
Most data governance training is self-paced and tool-oriented, built for practitioners configuring a platform. This program is built for executives who hold decision-making authority. Each session pairs the underlying concepts with the decisions a leader actually has to make: where to set risk tolerance, who should be accountable, whom to engage, what to fund, and what to assess before operationalizing data and AI.
How does the program handle AI and agentic systems?
AI does not replace data governance; it raises the stakes. A dedicated session extends your existing program across the full model lifecycle and into agentic systems — covering the unique hazards of autonomous execution, training-data integrity, model risk and lifecycle oversight, EU AI Act obligations, transparency artifacts, non-human identity and access management, and human-in-the-loop accountability.
Who should we enroll?
A cross-functional leadership cohort: the chief data or analytics officer, data owners, and the technology, risk, compliance, legal, and business leaders who set data policy and answer for outcomes. The program is built to be brought as a team and is often sponsored by an L&D or learning leader.
Do participants need a technical background?
No. The program assumes decision-making authority, not technical skill. The first session builds shared vocabulary so technology, compliance, legal, and business functions can discuss data and AI risk in the same terms.
What is the standard program design?
A single eight-hour day across seven sessions, moving from foundational vocabulary to a board-ready governance deliverable. The cohort builds an end-to-end program and completes a one-page executive strategy summary as a capstone. This is the baseline we tailor to your organization.
What frameworks and regulations does the program use?
Four reference points: DAMA-DMBOK 3.0 for the disciplines of governance, quality, metadata, and lineage; the data-protection and sector regulations (GDPR, CCPA, HIPAA, PCI-DSS); the NIST AI Risk Management Framework 1.0 for a shared AI-risk vocabulary; and the EU AI Act for risk-tiered obligations on high-risk AI systems.
What will our team produce?
A board-ready, one-page executive data-governance strategy — operating model and stewardship structure, tooling architecture, regulatory posture and control mapping, an AI/ML and agentic governance approach, and a 12-month implementation roadmap with measurable milestones — plus a shared governance language the team can apply across future initiatives.
What formats and durations are available?
Any format and location — live online, on-site, or hybrid. The standard design runs as a single eight-hour day; time, duration, and cadence are client-definable and set with your team.
Are CEUs available?
Continuing Education Units (CEUs) are available for this program. A professional certificate from Caltech and a letter of completion are provided.
How do we get started?
Submit an inquiry and the CTME team will contact you to scope a tailored program for your organization.
