COMPEL Glossary / data-steward
Data Steward
A data steward is an individual formally responsible for the quality, governance, and appropriate use of data within a specific domain or business function.
What this means in practice
Data stewards ensure that data meets quality standards and governance policies before it is used for AI training or operations. They serve as the bridge between data governance policy and operational practice -- translating enterprise data standards into domain-specific requirements and monitoring compliance. In the COMPEL maturity model, the presence and effectiveness of data stewards is a key indicator assessed in Domain 6 (Data Management and Quality). At Level 2, stewards may be identified but the role is informal. At Level 3, stewards are formally appointed with defined responsibilities, trained in governance practices, and accountable for quality within their domains.
Why it matters
Data stewards serve as the critical bridge between data governance policy and operational practice. Without them, governance standards remain theoretical documents that development teams ignore or interpret inconsistently. Effective stewardship ensures that data entering AI pipelines meets quality and compliance requirements, preventing downstream failures that are far more expensive to fix after models are trained and deployed.
How COMPEL uses it
The presence and effectiveness of data stewards is a key indicator assessed in Domain 6 (Data Management and Quality) during Calibrate. At Level 2, stewards may be identified but informal. At Level 3, stewards are formally appointed with defined responsibilities. During Organize, stewardship roles are established as part of the operating model. The Evaluate stage measures steward effectiveness through data quality metrics.
Related Terms
Other glossary terms mentioned in this entry's definition and context.