Difference between revisions of "Data Stewardship"
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| − | <ref>DAMA-DMBOK2, 1.3.4 Data Stewardship, | + | ''Data Stewardship''<ref>DAMA-DMBOK2, 1.3.4 Data Stewardship, p.75,76</ref> is the most common label to describe accountability and responsibility for data and processes that ensure effective control and use of data assets. Stewardship can be formalized through job titles and descriptions, or it can be a less formal function driven by people trying to help and organization get value from its data. |
In most cases, data stewardship activities will focus on some, if not all, of the following: | In most cases, data stewardship activities will focus on some, if not all, of the following: | ||
| − | * '''Creating and managing core | + | * '''Creating and managing core metadata''': Definition and management of business terminology, valid data values, and other critical metadata. Stewards are often responsible for an organization's Business Glossary, which becomes the system of record for business terms related to data. |
* '''Documenting rules and standards''': Definition/documentation of business rules, data standards, and data quality rules. Expectations used to define high quality data are often formulated in terms of rules rooted in the business processes that create or consume data. Stewards help surface these rules in order to ensure that there is consensus about them within the organization and that they are used consistently. | * '''Documenting rules and standards''': Definition/documentation of business rules, data standards, and data quality rules. Expectations used to define high quality data are often formulated in terms of rules rooted in the business processes that create or consume data. Stewards help surface these rules in order to ensure that there is consensus about them within the organization and that they are used consistently. | ||
* '''Managing data quality issues''': Stewards are often involved with the identification and resolution of data related issues or in facilitating the process of resolution. | * '''Managing data quality issues''': Stewards are often involved with the identification and resolution of data related issues or in facilitating the process of resolution. | ||
* '''Executing operational data governance activities''': Stewards are responsible for ensuring that, day-to-day and project-by-project, data governance policies and initiatives are adhered to. They should influence decisions to ensure that data is managed in ways that support the overall goals of the organization. | * '''Executing operational data governance activities''': Stewards are responsible for ensuring that, day-to-day and project-by-project, data governance policies and initiatives are adhered to. They should influence decisions to ensure that data is managed in ways that support the overall goals of the organization. | ||
| − | <references /> | + | <br /><br />According to [https://datagovernance.com/the-data-governance-basics/governance-and-stewardship The Data Governance Institute]: "Data Stewardship is concerned with taking care of data assets that do not belong to the stewards themselves. Data Stewards represent the concerns of others. Some may represent the needs of the entire organization. Others may be tasked with representing a smaller constituency: a business unit, department, or even a set of data themselves."<ref><nowiki>https://datagovernance.com/the-data-governance-basics/governance-and-stewardship/</nowiki></ref><br><br> |
| + | |||
| + | // "We want to make sure that a data producer is held accountable for the data they are producing. We can achieve this effectively by defining '''''Data Stewardship''''' within our organization." | ||
| + | |||
| + | === See also: === | ||
| + | [[Data Steward]]<br><br><references /> | ||
Latest revision as of 14:48, 22 January 2022
Data Stewardship[1] is the most common label to describe accountability and responsibility for data and processes that ensure effective control and use of data assets. Stewardship can be formalized through job titles and descriptions, or it can be a less formal function driven by people trying to help and organization get value from its data.
In most cases, data stewardship activities will focus on some, if not all, of the following:
- Creating and managing core metadata: Definition and management of business terminology, valid data values, and other critical metadata. Stewards are often responsible for an organization's Business Glossary, which becomes the system of record for business terms related to data.
- Documenting rules and standards: Definition/documentation of business rules, data standards, and data quality rules. Expectations used to define high quality data are often formulated in terms of rules rooted in the business processes that create or consume data. Stewards help surface these rules in order to ensure that there is consensus about them within the organization and that they are used consistently.
- Managing data quality issues: Stewards are often involved with the identification and resolution of data related issues or in facilitating the process of resolution.
- Executing operational data governance activities: Stewards are responsible for ensuring that, day-to-day and project-by-project, data governance policies and initiatives are adhered to. They should influence decisions to ensure that data is managed in ways that support the overall goals of the organization.
According to The Data Governance Institute: "Data Stewardship is concerned with taking care of data assets that do not belong to the stewards themselves. Data Stewards represent the concerns of others. Some may represent the needs of the entire organization. Others may be tasked with representing a smaller constituency: a business unit, department, or even a set of data themselves."[2]
// "We want to make sure that a data producer is held accountable for the data they are producing. We can achieve this effectively by defining Data Stewardship within our organization."
