Data & AI Training
Policies & Standards
Creating clear, enforceable rules for data that people actually understand and follow.
Overview
Policies and standards are essential to governance, yet they are often over-engineered, ignored or disconnected from how people work. This session focuses on how to design data policies and standards that are clear, proportionate and enforceable.
Participants learn how to move beyond “policy for policy’s sake” and instead create a small, effective set of rules that support consistency, quality, risk management and decision-making. The emphasis is on lifecycle, ownership and adoption, not just documentation.
Who it is for
- Governance and risk leaders defining data policies.
- Data Owners and Stewards accountable for compliance.
- Legal, compliance and assurance teams interfacing with data.
- Transformation leaders embedding governance into delivery.
What you will learn
- The role of policies and standards within governance.
- The difference between principles, policies and standards.
- How to design policies that are proportionate and actionable.
- How to approve, communicate and maintain policies over time.
- How standards support quality, interoperability and reuse.
- Why most policy libraries fail and how to avoid it.
Agenda
- Why policies fail in practice.
- Principles vs policies vs standards.
- Policy lifecycle: create, approve, communicate, enforce.
- Ownership and accountability models.
- Exceptions, waivers and pragmatic governance.
- Examples of effective data policies.
- Q&A and discussion.
Delivery and format
Delivered as a 1 hour interactive virtual session. Can be extended into a policy design workshop.
- Format: Live virtual or on site.
- Group size: Up to 25 participants recommended.
- Optional: Follow-up policy design workshop.
Next steps
This course is commonly paired with: DG4 · Metadata Management, DG6 · Issues Management and DQ1 · Foundations of Data Quality