What is Data Stewardship?
Data Stewardship has, as its main objective, the management of the corporation’s data assets in order to improve their reusability, accessibility, and quality. It is the Data Stewards’ responsibility to approve business naming standards, develop consistent data definitions, determine data aliases, develop standard calculations and derivations, document the business rules of the corporation, monitor the quality of the data in the data warehouse, define security requirements, and so forth.
Just as the demand for a data warehouse with good data has grown, the need for a Data Stewardship function has likewise grown. More and more companies are recognizing the critical role this function serves in the overall quest for high quality, available data. Such an integrated, corporate-wide view of the data provides the foundation for the shared data so critical in the data warehouse.
What is the scope of a Data Steward?
A typical corporate Data Stewardship function should have one Data Steward assigned to each major data subject area. These subject areas consist of the critical data entities or subjects such as Customer, Order, Product, Market Segment, Employee, Organization, Inventory, etc. Usually, there are about 15-20 major subject areas in any corporation. As an example, one Data Steward would be responsible for the Customer subject area and another would be assigned to the Product subject area.
The Data Steward responsible for a subject area usually works with a select group of employees representing all aspects of the company for that subject area. This committee of peers is responsible for resolving integration issues concerning their subject area. The results of the committee’s work are passed on to the Data Administration and Database Administration functions for implementation into the corporate data models, meta data repository, and ultimately, the data warehouse construct itself.
Just as there is a Data Architect in most Data Administration functions, there should be a “lead” Data Steward responsible for the work of the individual Data Stewards. The lead Data Steward’s responsibility is to determine and control the domain of each Data Steward. These domains can become muddy and unclear, especially where subject areas intersect. Political battles can develop between the Data Stewards if their domains are not clearly established.
Where to look for a good Data Steward?
Data Stewards generally come from either the end user community or the IT department.
Subject matter experts from within the end user community make good Data Stewards. They are quite knowledgeable about specific parts of the corporation. However, they may need training in some of the technical aspects of data models and IT systems. In addition, they must be familiar with business areas other than their own. Otherwise they can be perceived as biased toward their perspectives on the data.
Data modelers from the IT Data Administration function also make good Data Stewards. They understand the technical issues of data integration and usually acquire a great deal of exposure to the business community while modeling the business rules, data entities and attributes. In addition, they generally have good rapport with end users and Database Administrators alike. However, the resources must have the respect of the end user community and the authority to make decisions on their behalf.
A final note on the importance of Data Stewardship
The Data Stewardship position probably has the highest profile within the corporation of the three mentioned above. Why? Because the Data Steward acts as the conduit between IT and end users. They have the difficult but very rewarding task of guaranteeing that one of the corporation’s most critical assets, its data, is used to its fullest capacity.
For Data Stewardship to succeed in your corporation, a new incentive paradigm must be developed – one that rewards people on the basis of horizontal integration rather than only vertical or “bottom line” success. As long as a department or division is solely focused on its bottom line, it will see no benefit in changing its business practices to integrate data and business rules with another department or division. The new incentives should be driven by the success of the groups to resolve integration issues, to develop unified definitions, to change business practices to conform to the new standards, etc.
Data Integration Issues
Data Stewards are responsible for the following:
Standard Business Naming Standards
Standard Entity Definitions
Standard Attribute Definitions
Business Rules Specification
Standard Calculation and Summarization Definitions
Entity and Attribute Aliases
Data Quality Analyses
Sources of Data for the Data Warehouse
Data Security Specification
Data Retention Criteria
A Data Stewardship Program
In today’s environment, therefore, maximizing the accessibility, reusability, and quality of a company’s data is an essential survival tool. A data stewardship program can achieve those goals. A number of best practices for such programs have now emerged.
First, as with any major corporate initiative, senior management must be fully engaged. Second, the business and technical sides must work closely together in cross-functional teams that include representatives from marketing underwriting, finance, legal, and technical. These teams are responsible for:
Business naming standards
Consistent data definitions
Developing standard calculations and derivations
Documenting the business rules of the corporation
Monitoring the quality of the data in the data warehouse
Cross-functional teams ensure that business people understand their role in maintaining the quality of the data. Moreover, by increasing their awareness of what data exists and where they can find it, they are more likely to maximize their use of the data. From the other side, technical people gain insights that allow them to fully align their work priorities with the company’s overall business strategy.
Data Stewardship: Person responsible for managing the data in a corporation in terms of integrated, consistent definitions, structures, calculations, derivations, and so on.
Data Stewardship: A Framework for Achieving and Maintaining Data Integrity in the Data Warehouse.