Meta Data in Data Governance

By Anne Smith

Data Governance is the practice of managing information to identify and improve its business value.  Data governance provides a practical methodology for data with business priorities.  Although meta data is not new, its importance to effective data governance has recently been receiving attention as a critical element for maintaining the value of the organization’s data.  Meta data provides the means for identifying and classifying data within subject areas and enabling users and technologists to manage the context as well as the content in information systems.

Simply put, meta data is “data about data,” and it generally defines the content of a data object.   Meta data within data governance has the primary functions of enabling policy and providing access to data. The policies enabled include data definition, data usage, data security and data lineage and heritage.  Although governance and policies are created to determine the appropriate actions to be applied to a given data object, ultimately they must be applied to the physical storage of the information as well.

Meta data provides the linkage between the business need or desire (policy) and the information or data value. The effective management of meta data is one of the essential activities of a data steward within a governance practice, enabling data management policy and access to information.  Meta data management refers to the activities associated with ensuring that meta data is created/captured at the point of file creation and that the broadest possible portfolio of meta-information is collected, stored in a repository for use by multiple applications, and controlled to remove inconsistencies and redundancies. In short, data governance uses meta data management to impose management discipline on the collection and control of data.

Organizations will benefit from a comprehensive view of their meta data, and of meta data management, when they fully understand its implications. Meta data can be the center of the data governance effort, since understanding the context of the data content is the central concept of data stewardship.  To achieve the business benefits of enterprise data management, the connection between the data instances and the various forms of meta data associated with each instance of data becomes an asset to be managed for competitive advantage.

The concept of collecting data about data has been around for years. However, many organizations that embark on a data governance practice do not understand fully the need for their data stewards to manage meta data as well as the actual data values.  Data governance policies should include all of the appropriate meta data policies, and good data stewardship training should include education and training in meta data and its management.

Meta data management refers to the activities associated with ensuring that meta data is properly created, stored, and controlled so that the data is consistently defined across the enterprise.  This definition should point out the importance of meta data management within a governance practice, since governance creates the policies for the appropriate usage of data within an organization.

Capturing meta data at the point of object creation is critical to ensuring that it will be captured at all.  Numerous silos of archived data exist today in most enterprises.  Finding a specific instance of data or finding a content-based requirement across multiple objects may be difficult at best and impossible at worst in organizations that do not have good meta data management as part of the governance practice.  Good stewardship that has implemented good data governance should make this discovery and usage possible and practical.

Storing meta data in a common repository enhances its usability. Intelligent management of any resource implies the ability to view and share that resource across applications; this is the logical approach to managing meta data. Physical centralization is not required and may be undesirable within an organization’s architecture.  IT governance, a companion to data governance, will determine how this logical organization of meta data is implemented.

Stewarding meta data ensures that the data will have value to support the business needs and decision making. Stewardship is the implementation of data governance practices, providing the actual users of data with value and context for understanding the data and its components.

Data stewardship for meta data would include:

  • Creating and documenting the data definitions for the subject area’s entities and attributes;
  • Identifying the business and architectural relationships between objects;
  • Certifying  the accuracy, completeness and timeliness of the content;
  • Establishing and documenting the context of the content (data heritage and lineage);
  • Providing a range of contextual understanding for an increasingly diverse range of data users, including  trusted data for compliance, internal controls, and better decision-making;
  • Providing some of the information a technology professional might need for the physical implementation.

Metadata management is a critical component of any robust data governance practice, and meta data is one of the foundational contributors to creating and maintaining full business value of an organization’s data.

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 amsmith@ewsolutions.com

 
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