Metadata in Data Governance

One definition of data governance is the practice of managing information to identify and improve its business value. Data governance provides a practical methodology for ensuring that data is aligned with business priorities and that the data is defined as the organization has decided it will be defined, consistently.

Although metadata 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. Metadata provides the means for identifying, defining, and classifying data within subject areas and enabling users and technologists to manage the context as well as the content of the assets in information systems.

Simply put, metadata is “data about data,” and it generally defines the content of a data object. Metadata within the data governance practice has the primary responsibility of enabling policy and providing access to data. These policies include those concerned with data definition, data usage, data security and data lineage and heritage. It is important to remember that 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. Metadata will assist in both business and technical instantiations of the data, making it a very powerful part of the data governance practice’s set of tools.

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, thus enabling data management policy and access to information. Metadata management refers to the activities associated with ensuring that meta data is created/captured at the point of the data’s 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 and discipline on the collection and control of data.

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 meta data and its management.

Organizations will benefit from a comprehensive view of their metadata, and of metadata management. If an organization fully understands the value of metadata management, they will implement the proper management and technical solutions that enable the discovery and collection of all forms of meta data – both business and technical. Metadata 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. Some forms of meta data that may be overlooked include business rules, calculations, algorithms, data usage patterns – these are as important as the basic definitions and data types/formats most usually associated with the term “metadata.”

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 governance practice, since governance creates the policies for the appropriate usage of data within an organization.

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 governance practice. Good stewardship that has been implemented via good data governance 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 always required for metadata management, and may be undesirable within an organization’s architecture.  However, no approach to repository architecture should be ignored at the start of the initiative, since the best architecture may not be evident immediately. IT governance, a companion to data governance, will determine how this logical organization of metadata is implemented to the continued benefit of the entire organization.

Stewarding metadata 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 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.
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.

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