Developing a Meta Data Strategy – Data Governance’s Role

By Anne Smith

Traditional systems development and implementation has focused on processes, rather than on data as the foundation of the enterprise.  A data orientation led by data governance represents a major cultural change.  It is not only a change in the way an organization delivers information, it also implies a new way of perceiving, accessing and respecting the evolving asset of information by the business community.

The movement toward a data governance orientation can be challenging for traditionally organized enterprises, since many in both the business and IT were not taught the fundamental importance of data and the corresponding importance of the meaning of that data.  Data is much more stable than process or organization.  Success in developing a data governance program and instantiating that approach requires strong change agents and a set of carefully orchestrated plans.   Sometimes, developing a truly effective data governance program requires some reengineering of the IS and business organizations to explain and enforce the collection, management and understanding of the meaning of the data used and stored by the enterprise.

Data governance and the data stewards that form the foundation of the governance program are responsible for the data instances (values) and the meta data for that data.  Therefore, it is important that any data governance program include the development and implementation of a meta data strategy.

A meta data strategy can assist in the achievement of the goals of data governance by providing a focus for sharing the data assets of an organization.  As the governance program offers recognition to the value of data and its components and usage within and throughout the organization, a meta data strategy can provide a map for managing the expanding requirements for information that the business places upon the environment.  A meta data strategy highlights the importance of a central data governance organization that will focus on data quality, integrity and reuse. Finally, development and implementation of a meta data strategy enables an organization to begin to measure the value of the information assets under their control. The purchase or development of a meta data storage facility / meta data database can assist data governance and the data stewards in the management of meta data for a data warehouse and / or other enterprise initiatives.

The components of a meta data strategy could include:

  • Organizational meanings of meta data and its role in the organization
  • Business challenges and issues that can be addressed by improved meta data
  • Approach to data governance
  • Data stewardship roles for all main subject areas and key data
  • Meta data usage guidelines
  • Identifying sources of meta data
  • Overview of process to determine the quality of the meta data sources (absolute, relative, historical, etc.)
  • Methods to consolidate meta data from multiple sources
  • Identifying where meta data will be stored
  • Determining responsibility for proper use, quality control and meta data update procedures
  • Establishing meta data standards and procedures
  • Measuring the use and effectiveness of the meta data


The Data Governance Committee or Council, comprised of business data stewards and members of the Information Resource Management function (data analysts, database analysts), is the group that is responsible for implementing the concepts outlined in the meta data strategy.  This team decides what order will be used to fulfill the requirements in the strategy and the content of the list above.  Frequently, data governance councils use consultants to assist them in the development of a meta data strategy and implementation of the strategy’s components since this is a specialized area in data management.

Enterprise or corporate data models often serve as one of the first discovery areas for meta data management, and the development of data warehouses or data marts is cited as one of the main reasons companies adopt a meta data strategy – to understand the data that is resident in their systems and to make more efficient use of that data as a corporate resource.  With the resurgence of the data warehousing approach to business intelligence, the importance of meta data is growing continually, and the central role of data governance is becoming more apparent.

The development and implementation of an effective meta data strategy enables a company to address the true information needs of the business community and promulgates the importance of data for the benefit of the company.  Meta data can be called “the foundation” of an organization’s success in realizing the potential value of its data and information, to achieve competitive advantage.

About the Author

Anne Marie Smith is a leading consultant in Information Management and is a frequent contributor to various IS publications. Anne Marie has over 20 years experience in information management for several corporate entities and has successfully led the development of data resource management departments within corporations and consulting organizations. Anne Marie is active in the local chapter of DAMA and serves on the board of directors of DAMA International, and is an advisor to the DM Forum. She has been an instructor of Management Information Systems (MIS) with Philadelphia, PA area colleges and universities. Anne Marie has taught topics such as: data stewardship and governance, data warehousing, business requirements gathering and analysis, metadata management and metadata strategy, information systems and data warehouse project management. Anne Marie’s areas of consulting expertise include metadata management including data stewardship and governance, information systems planning, systems analysis and design, project management, data warehouse systems assessment and development, information systems process improvement and information resource management/data resource management. Anne Marie holds the degrees Bachelor of Arts and a Master's of Business Administration in Management Information Systems from La Salle University; she has earned a PhD in MIS at Northcentral University. She is a certified logical data and process modeler and holds project management certification. Anne Marie can be reached at

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