What Are 3 Specific Examples Of A Data Stewards Work

Approaches to Assigning Data Ownership and Stewardship

Organizations tin take multiple approaches to assigning Data Owners and Data Stewards for enterprise data. In doing so, they need to consider several factors and answer the post-obit questions.

Question #1:

Should we tie ownership/stewardship to data types?

Accountabilities may be tied to a blazon of data that may exist

Principal Data
Transactional Data
Reference Information
Metadata
Historical Data
Temporary Data
or other types

Best Practice: Almost organizations respond "aye" to this question. Stewards or others who are assigned data-related responsibilities are expected to work with but one or a few types of data rather than all types.

Question #ii:

For what data subject areas will we first assign ownership/stewardship?

Information-related or metadata-related accountabilities that focus on Master Data may be tied to different subject field areas, such every bit:

Customers
Products
Locations
Organizational hierarchies
etc.

Best Practice: Information Governance pilot projects often strive to govern a manageable set of data elements within a single subject expanse. Accountabilities are assigned to standardize data elements, specify and enforce valid values, and address data quality.

Question #3:

How should nosotros assign ownership/stewardship to data discipline areas?

Some organizations assign an Enterprise Data Steward with ultimate accountability for data within a subject or domain. Others create communities of Data Stewards and others who piece of work with that information. Another approach is to tie accountabilities to a Master Data Management program rather than to stewardship. And still another approach is to assign data-related responsibilities to functional roles rather than to stewards.

Question #4:

At what level of granularity should nosotros assign ownership/stewardship?

Information-related accountabilities may be tied to dissimilar levels of granularity of information.

Documents
Content units (used in documents, web displays, reports, etc.)
Data feeds
Data records
Raw data
- Domains of data (for example, all data related to Customers)
- Usage-related collections of data (for example, all fields appearing on a certain report, or all fields included in a compliance mandate such every bit HIPAA, HMDA, or Sarbanes-Oxley)
- Specific data entities (for example, within a data feed, an entire a Customer tape, including the client's ID, name, and all related data)
- Data attributes (for example, only a certain preference flag within a customer record)

All-time Exercise: Virtually organizations getting started with Information Governance and Stewardship feel that assigning all levels of granularity simultaneously is a "boil the ocean" type of fault. Instead, they choose certain levels of accountability for certain data, and so aggrandize scope over time.

Question #five:

Should nosotros tie data ownership/stewardship to processes and data flows?

Some organizations assign just one Data Possessor or Data Steward for a data element or bailiwick area. This person is responsible for the data no matter where it appears in an organization. This approach is not feasible for near organizations, however, with complicated data flows.

An alternative is assigning accountabilities for only a few segments in a data flow. 1 or more Data Stewards or SMEs could be responsible for admission command, quality, or typical Master Data responsibilities for specific data within those segments.

Question #6:

Should we tie data buying/stewardship to compliance and/or usage?

Some organizations assign accountabilities for related sets of data. For example, HIPAA requires protections of personally identifiable information; some organizations put teams in place to locate that data across systems, to specify controls for the information, and to monitor compliance. Also, some lending institutions may assign accountabilities to review all data discipline to Dwelling Mortgage Disclosure Human action (HMDA) compliance.