A data steward is an oversight or

data governance Data governance is a term used on both a macro and a micro level. The former is a political concept and forms part of international relations and Internet governance; the latter is a data management concept and forms part of corporate data govern ...

role within an organization, and is responsible for ensuring the quality and fitness for purpose of the organization's data assets, including the

metadata Metadata is "data that provides information about other data", but not the content of the data, such as the text of a message or the image itself. There are many distinct types of metadata, including: * Descriptive metadata – the descriptive ...

for those data assets. A data steward may share some responsibilities with a

data custodian In data governance groups, responsibilities for data management are increasingly divided between the business process owners and information technology (IT) departments. Two functional titles commonly used for these roles are data steward and data ...

, such as the awareness, accessibility, release, appropriate use, security and management of data. A data steward would also participate in the development and implementation of data assets. A data steward may seek to improve the quality and fitness for purpose of other data assets their organization depends upon but is not responsible for. Data stewards have a specialist role that utilizes an organization's

processes, policies, guidelines and responsibilities for administering an organizations' entire data in compliance with policy and/or regulatory obligations. The overall objective of a data steward is the

data quality Data quality refers to the state of qualitative or quantitative pieces of information. There are many definitions of data quality, but data is generally considered high quality if it is "fit for tsintended uses in operations, decision making and ...

of the data assets, datasets, data records and data elements. This includes documenting metainformation for the data, such as definitions, related rules/governance, physical manifestation, and related data models (most of these properties being specific to an attribute/concept relationship), identifying owners/custodian's 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 data assets and elements which they will steward, with the ultimate result being standards,

control Control may refer to: Basic meanings Economics and business * Control (management), an element of management * Control, an element of management accounting * Comptroller (or controller), a senior financial officer in an organization * Controlli ...

s and

data entry Data entry is the process of digitizing data by entering it into a computer system for organization and management purposes. It is a person-based process and is "one of the important basic" tasks needed when no machine-readable version of the inf ...

. The steward works closely with business glossary standards analysts (for standards), with

data architect A data architect is a practitioner of data architecture, a data management discipline concerned with designing, creating, deploying and managing an organization's data architecture. Data architects define how the data will be stored, consumed, inte ...

modeler In 3D computer graphics, 3D modeling is the process of developing a mathematical coordinate-based representation of any surface of an object (inanimate or living) in three dimensions via specialized software by manipulating edges, vertices, an ...

s (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.

Master data management Master data management (MDM) is a technology-enabled discipline in which business and information technology work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise's official shared ...

often 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

A data steward ensures that each assigned data element: # Has clear and unambiguous

data element definition In metadata, a data element definition is a human readable phrase or sentence associated with a data element within a data dictionary that describes the meaning or semantics of a data element. Data element definitions are critical for external use ...

# Does not conflict with other data elements in the metadata registry (removes duplicates, overlap etc.) # Has clear enumerated value definitions if it is of type

Code In communications and information processing, code is a system of rules to convert information—such as a letter, word, sound, image, or gesture—into another form, sometimes shortened or secret, for communication through a communicati ...

# Is still being used (remove unused data elements) # Is being used consistently in various computer systems # Is being used, fit for purpose = Data Fitness # Has adequate documentation on appropriate usage and notes # Documents the origin and sources of authority on each metadata element # Is protected against unauthorised access or change Responsibilities of data stewards vary between different organisations and institutions. For example, at Delft University of Technology, data stewards are perceived as the first contact point for any questions related to research data. They also have subject-specific background allowing them to easily connect with researchers and to contextualise data management problems to take into account disciplinary practices.

Types of data stewards

Depending on the set of data stewardship responsibilities assigned to an individual, there are 4 types (or dimensions of responsibility) of data stewards typically found within an organization: # Data object data steward - responsible for managing reference data and attributes of one business data entity # Business data steward - responsible for managing critical data, both reference and transactional, created or used by one business function # Process data steward - responsible for managing data across one business process # System data steward - responsible for managing data for at least one IT system

Benefits of data stewardship

Systematic data stewardship can foster: # Faster analysis # Consistent use of data management resources # Easy mapping of data between computer systems and exchange documents # Lower costs associated with migration to (for example)

Service Oriented Architecture In software engineering, service-oriented architecture (SOA) is an architectural style that focuses on discrete services instead of a monolithic design. By consequence, it is also applied in the field of software design where services are provide ...

(SOA) # Better control of dangers associated with privacy, legal, errors, etc. Assignment of each data element to a person sometimes seems like an unimportant process. But many groups have found that users have greater trust and usage rates in systems where they can contact a person with questions on each data element.

Examples

Delft University of Technology (TU Delft) offers an example of data stewardship implementation at a research institution. In 2017 the Data Stewardship Project was initiated at TU Delft to address research data management needs in a disciplinary manner across the whole campus. Dedicated data stewards with subject-specific background were appointed at every TU Delft faculty to support researchers with data management questions and to act as a linking point with the other institutional support services. The project is coordinated centrally by TU Delft Library, and it has its own website, blog and a YouTube channel. Th

nited States Environmental Protection Agency, EPA metadata registry furnishes an example of data stewardship. Note that each data element therein has a "POC" (point of contact).

Data stewardship applications

A new market for data governance applications is emerging, one in which both technical and business staff — stewards — manage policies. These new applications, like previous generations, deliver a strong business glossary capability, but they do not stop there. Vendors are introducing additional features addressing the roles of business in addition to technical stewards' concerns. Information stewardship applications are business solutions used by business users acting in the role of information steward (interpreting and enforcing information governance policy, for example). These developing solutions represent, for the most part, an amalgam of a number of disparate, previously IT-centric tools already on the market, but are organized and presented in such a way that information stewards (a business role) can support the work of information policy enforcement as part of their normal, business-centric, day-to-day work in a range of use cases. The initial push for the formation of this new category of packaged software came from operational use cases — that is, use of business data in and between transactional and operational business applications. This is where most of the master data management efforts are undertaken in organizations. However, there is also now a faster-growing interest in the new data lake arena for more analytical use cases. Some of the vendors in Metadata Management, like Alation, have started highlighting the importance of Data Stewards to employees interested in using data to make business decisions.

Data steward responsibilities

Types of data stewards

Benefits of data stewardship

Examples

Data stewardship applications

See also

References

Further reading