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Metadata Management in a Data Governance Program

Metadata Management in a Data Governance Program

Metadata management is an essential companion discipline for every successful data governance program

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 metadata is not a new concept, its importance to effective data governance has become more apparent as a critical element for maintaining the value of the organization’s data.  Metadata 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.

Metadata Definition

Simply put, metadata is “data about data,” and it defines the content of a data object (“the context of the content”).  Metadata’s role within data governance has the primary functions of enabling policy and providing access to data.  These data governance policies include data definition, data usage, data security and data lineage and heritage.  Although data governance programs create policies to determine the appropriate actions to be applied to a given data object for business purposes, ultimately they must be applied to the physical storage of the information as well.

Metadata provides the linkage between the business need or desire (policy) and the information or data value.  The effective management of metadata is one of the essential activities of a data steward within a governance practice, enabling data management policy and access to information.  Metadata management refers to the activities associated with ensuring that Metadata 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 metadata management to impose management discipline on the collection and control of data.

Value of Metadata Management

Organizations will benefit from a comprehensive view of their metadata, and of metadata management, when they fully understand its value and the implications of not having accurate context for their data.  Metadata can be the center of the data governance effort, since understanding the context of the data content is one of the central activities of data stewardship.  To achieve the business benefits of enterprise data management, the connection between the data instances and the various forms of Metadata 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 metadata as well as the actual data values.  Data governance policies should include all of the appropriate metadata policies, and good data stewardship training should include education and training in metadata and its management.

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

Metadata Activities

Capturing metadata 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 metadata management as part of the data governance practice.  Good data stewardship that is implemented along with good data governance and robust metadata management should make this discovery and usage possible and practical.

Storing metadata 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 metadata.  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 metadata is implemented.

Assigning data stewards to be responsible for metadata as well as for the data content ensures that the data will have the correct meaning / context to support the business needs and decision making.  Data 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 metadata 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.

Conclusion

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

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Anne Marie Smith, Ph.D.

Anne Marie Smith, Ph.D. is an internationally recognized expert in the fields of enterprise data management, data governance, enterprise data architecture and data warehousing. Dr. Smith is VP of Education and Chief Methodologist of Enterprise Warehousing Solutions, Inc. (EWS), a Chicago-based enterprise data management consultancy dedicated to providing clients with best-in-class solutions. Author of numerous articles and Fellow of the Institute for Information Management (IIM), Dr. Smith is also a well-known speaker in her areas of expertise at conferences and symposia.

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