Acronym for eXtensible Markup Language – the markup language used to convey the definition, structure, and meaning of information contained in a document. Originally, SQL stood for Structured Query Language. Well, the letters SQL have no meaning ascribed to them. SQL is the database language defined in the international standards ISO/IEC 9075, the last edition of which was published in 2003. The language contains the constructs required for data definition, data querying, and data manipulation. Most relational database management system vendors use a SQL version that matches the version specified in the standards. Storing metadata in a common repository improves the user experience. Intelligent management of each resource involves the ability to view and share that resource across applications. This is the logical approach to metadata management. Physical centralization is not always necessary for metadata management and can be undesirable within an organization`s architecture. However, at the beginning of the initiative, no approach to repository architecture should be ignored, as the best architecture may not be immediately apparent.
IT governance, a companion to data governance, determines how this logical organization of metadata is implemented for the continued benefit of the entire organization. Simply put, metadata is “data about data” and typically defines the content of a data object. Metadata in data governance practice has the primary responsibility for setting up policies and providing access to data. These policies include those that address data definition, data use, data security, origin and data heritage. It is important to remember that while governance and policies are created to determine the appropriate actions to apply to a particular data object, they must ultimately also be applied to the physical storage of information. Metadata helps in the commercial and technical instantiation of data, making it a very powerful part of the tools of data governance practice. Capturing metadata at the time of object creation is essential to ensure that it is captured in the first place. In most companies today, there are many silos of archived data. Finding a specific instance of data or finding a content-based query across multiple objects can be difficult at best and impossible at worst in organizations that don`t have good metadata management as part of governance practices. Good stewardship, implemented through good data governance, should make this discovery and use possible and achievable. (i) An abstract and autonomous logical definition of the data structures and associated operators that make up the abstract machine with which users interact (for example, the relational data model).
(ii) A persistent data model of an organization (for example, a data entity relationship model needed to support a human resources department). Metadata represents the link between the company`s (political) need or desire and the value of the information or data. Effective metadata management is one of the essential activities of a data manager within a governance practice, enabling data management policies and access to information. Metadata management refers to the activities associated with creating/capturing metadata at the time of data creation and collecting the widest possible portfolio of meta-information, stored in a repository for use by multiple applications and controlled to eliminate inconsistencies and redundancies. In short, data governance uses metadata management to manage and discipline data collection and control. A description of the general logical structure of a database, expressed in a data definition language (for example, the data definition component of SQL). Software that stores, manipulates, and defines metadata – a data dictionary is usually associated with a software engineering support tool. i) The owner of a data definition is the person in the organization who has the power to say that the data must be retained and that this definition is the appropriate definition for the data. (ii) The owner of a data value is the person or entity authorized to change that value.
An enterprise service that helps provide information services by controlling or coordinating definitions and the use of reliable and relevant data. Role in data management that addresses the mechanisms for defining, controlling the quality and accessibility of an organization`s data. While metadata is not new, its importance for effective data governance has recently attracted attention as an essential element in maintaining the value of enterprise data. Metadata helps identify, define, and classify data across domains, allowing users and technologists to manage the context and content of assets in information systems. Metadata management ensures that data adds value to meet business needs and decision-making. Stewardship is the implementation of data governance practices that provide real data users with value and context to understand data and its components. The concept of collecting “data rather than data” has been around for years. However, many organizations that engage in a data governance practice do not fully understand that their data stewards need to manage metadata as well as the actual values of the data. Data governance policies should include all appropriate metadata policies, and good data management should include education and training on metadata and its management. A person who manages a data definition on behalf of the owner of the data definition. Companies get a complete view of their metadata and metadata management. When a company fully understands the value of metadata management, it implements the appropriate technical and management solutions that enable the discovery and collection of all forms of metadata, both commercial and technical.
Metadata can be at the center of data governance efforts, as understanding the context of data content is the central concept of data management. To reap the business benefits of enterprise data management, the connection between data instances and the different forms of metadata associated with each data instance becomes an asset that must be managed to gain a competitive advantage. Some forms of metadata that can be overlooked include business rules, calculations, algorithms, and data usage patterns – these are just as important as the basic definitions and data types/formats typically associated with the term “metadata.” Metadata management refers to the activities associated with the correct creation, storage, and control of metadata so that data is defined consistently across the enterprise. This definition should emphasize the importance of metadata management in a governance practice, as governance sets the guidelines for the appropriate use of data within an organization. Computerized information that doesn`t have a data structure that`s easy for a machine to read, including audio, video, and unstructured text like the body of a word processing document – basically, it`s the same as multimedia data. The logical structure of a relational database management system (RDBMS) table that matches the attribute of the relational data model.
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