Data steward

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A data steward is a person responsible for the management and fitness of data elements (also known as critical data elements) - both the content and metadata. Data stewards have a specialist role that incorporates processes, policies, guidelines and responsibilities for administering organizations' entire data in compliance with policy and/or regulatory obligations. A data steward may share some responsibilities with a data custodian.

The overall objective of a Data Steward is metadata management, in regard to the key/critical data elements existing within a specific enterprise operating structure, of the elements in their respective domains. This includes capturing/documenting (meta)information for their elements (such as: definitions, related rules/governance, physical manifestation, related data models, etc. With most of these properties being specific to an attribute/concept relationship), identifying owners/custodians/various responsibilities, relations insight pertaining to attribute quality, aiding with project requirement data facilitation and documentation of capture rules.

Data stewards begin the stewarding process with the identification of the elements which they will steward, with the ultimate result being standards, controls and data entry.[citation needed] The steward works closely with business glossary standards analysts (for standards), with data architect/modelers (for standards), with DQ analysts (for controls) and with operations team members (good-quality data going in per business rules) while entering data.

Data stewardship roles are common when organizations attempt to exchange data precisely and consistently between computer systems and to reuse data-related resources.[citation needed] Master data management often[quantify] makes references to the need for data stewardship for its implementation to succeed. Data stewardship must have precise purpose, fit for purpose or fitness.

Data Steward Responsibilities[edit]

A data steward ensures that each assigned data element:

  1. Has clear and unambiguous data element definition.
  2. Does not conflict with other data elements in the metadata registry (removes duplicates, overlap etc.)
  3. Has clear enumerated value definitions if it is of type Code.
  4. Is still being used (remove unused data elements)
  5. Is being used consistently in various computer systems
  6. Is being used, fit for purpose = Data Fitness
  7. Has adequate documentation on appropriate usage and notes
  8. Documents the origin and sources of authority on each metadata element
  9. Is protected against unauthorized access or change

Benefits of data stewardship[edit]

Systematic data stewardship can foster fitness thru:

  1. consistent use of data management resources
  2. easy mapping of data between computer systems and exchange documents
  3. lower costs associated with migration to (for example) Service Oriented Architecture (SOA)

Assignment of each data element to a person sometimes seems like an unimportant process. But many groups[which?] have found that users have greater trust and usage rates in systems where they can contact a person with questions on each data element.


The EPA metadata registry furnishes an example of data stewardship. Note that each data element therein has a "POC" (point of contact).

See also[edit]


  • Universal Meta Data Models, by David Marco and Michael Jennings, Wiley, 2004, page 93-94 ISBN 0-471-08177-9
  • Metadata Solution by Adrinne Tannenbaum, Addison Wesley, 2002, page 412
  • Building and Managing the Meta Data Repository, by David Marco, Wiley, 2000, pages 61–62
  • The Data Warehouse Lifecycle Toolkit, by Ralph Kimball et. el., Wiley, 1998, also briefly mentions the role of data steward in the context of data warehouse project management on page 70.
  • Developing Geospatial Intelligence Stewardship for Multinational Operations, by Jeff Thomas, US Army Command General Staff College, 2010,