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An entity–relationship model (or ER model) describes interrelated things of interest in a specific domain of knowledge. A basic ER model is composed of entity types (which classify the things of interest) and specifies relationships that can exist between entities (instances of those entity types).
Consider a database that records customer orders, where an order is for one or more of the items that the enterprise sells. The database would contain a table identifying customers by a customer number (primary key); another identifying the products that can be sold by a product number (primary key); and it would contain a pair of tables describing orders.
The enhanced entity–relationship (EER) model (or extended entity–relationship model) in computer science is a high-level or conceptual data model incorporating extensions to the original entity–relationship (ER) model, used in the design of databases.
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The C4 model relies at this level on existing notations such as Unified Modelling Language (UML), Entity Relation Diagrams (ERD) or diagrams generated by Integrated Development Environments (IDE). For level 1 to 3, the C4 model uses 5 basic diagramming elements: persons, software systems, containers, components and relationships.
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An entity–attribute–value model (EAV) is a data model optimized for the space-efficient storage of sparse—or ad-hoc—property or data values, intended for situations where runtime usage patterns are arbitrary, subject to user variation, or otherwise unforeseeable using a fixed design.
Equivalently, if the risk of an outcome is decreased by the exposure, the term absolute risk reduction (ARR) is used, and computed as . [ 2 ] [ 3 ] The inverse of the absolute risk reduction is the number needed to treat , and the inverse of the absolute risk increase is the number needed to harm .