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Descriptive metadata is typically used for discovery and identification, as information to search and locate an object, such as title, authors, subjects, keywords, and publisher. Structural metadata describes how the components of an object are organized. An example of structural metadata would be how pages are ordered to form chapters of a book.
Business metadata is important because it can greatly facilitate the usefulness of the data to business people. A simple example of business metadata is a glossary entry. Hover functionality in an application or web form can enable a glossary definition to be shown when cursor is on a field or term.
"The Marketing Taxonomy Assessment with Claravine reflects the results of our shared commitment, and the tool will provide brands with the insights they need to establish strong data standards and drive marketing success." The Marketing Taxonomy Assessment provides clients with a range of solutions, including: Taxonomy Review & Stakeholder ...
A good example of metadata is the cataloging system found in libraries, which records for example the author, title, subject, and location on the shelf of a resource. Another is software system knowledge extraction of software objects such as data flows, control flows, call maps, architectures, business rules, business terms, and database schemas.
The marketing plan also helps layout the necessary budget and resources needed to achieve the goals stated in the marketing plan. It is able to show what the company is intended to accomplish within the budget and also makes it possible for company executives to assess potential return on the investment of marketing dollars.
For example, in a federated Human Resources environment, the enterprise software may focus on storing people's data as current status, adding a few fields to identify the date of hire, date of last promotion, etc. However, this simplification can introduce business-impacting errors into dependent systems for planning and forecasting.
The ISO/IEC 11179 model is a result of two principles of semantic theory, combined with basic principles of data modelling. The first principle from semantic theory is the thesaurus type relation between wider and more narrow (or specific) concepts, e.g. the wide concept "income" has a relation to the more narrow concept "net income".
Tag cloud of a mailing list [1] A tag cloud with terms related to Web 2.0. A tag cloud (also known as a word cloud or weighted list in visual design) is a visual representation of text data which is often used to depict keyword metadata on websites, or to visualize free form text.
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