As the name implies, data owners are those individuals or groups within the organization that are in the position to obtain, create, and have significant control over the content (and sometimes, access to and the distribution of) the data. Data owners often belong to a business rather than a technology organization. For example, an insurance agent may be the owner of the list of contacts of his or her clients and prospects.

The concept of data stewardship is different from data ownership. Data stewards do not own the data and do not have complete control over its use. Their role is to ensure that adequate, agreed-upon quality metrics are maintained on a continuous basis. In order to be effective, data stewards should work with data architects, database administrators, ETL (Extract-Transform-Load) designers, business intelligence and reporting application architects, and business data owners to define and apply data quality metrics. These cross-functional teams are responsible for identifying deficiencies in systems, applications, data stores, and processes that create and change data and thus may introduce or create data quality problems. One consequence of having a robust data stewardship program is its ability to help the members of the IT organization to enhance appropriate architecture components to improve data quality.

Data stewards must help create and actively participate in processes that would allow the establishment of business-context-defined, measurable data quality goals. Only after an organization has defined and agreed with the data quality goals can the data stewards devise appropriate data quality improvement programs.

These data quality goals and the improvement programs should be driven primarily by business units, so it stands to reason that in order to gain full knowledge of the data quality issues, their roots, and the business impact of these issues, a data steward should be a member of a business team. Regardless of whether a data steward works for a business team or acts as a "virtual" member of the team, a data steward has to be very closely aligned with the information technology group in order to discover and mitigate the risks introduced by inadequate data quality.

Extending this logic even further, we can say that a data steward would be most effective if he or she can operate as close to the point of data acquisition as technically possible. For example, a steward for customer contact and service complaint data that is created in a company's service center may be most effective when operating inside that service center.

Finally, and in accordance with data governance principles, data stewards have to be accountable for improving the data quality of the information domain they oversee. This means not only appropriate levels of empowerment but also the organization's willingness and commitment to make the data steward's data quality responsibility his or her primary job function, so that data quality improvement is recognized as an important business function required to treat data as a valuable corporate asset.

References:

Master data management and customer data integration for a global enterprise By Alex Berson, Larry Dubov, Lawrence Dubov