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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.
Entity–relationship modeling is a database modeling method, used to produce a type of conceptual schema or semantic data model of a system, often a relational database, and its requirements in a top-down fashion. Diagrams created by this process are called entity-relationship diagrams, ER diagrams, or ERDs.
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).
System structure diagrams – another way to express the structure of a qualitative dynamic system Stock and flow diagrams - a way to quantify the structure of a dynamic system These methods allow showing a mental model of a dynamic system, as an explicit, written model about a certain system based on internal beliefs.
There is no single commonly accepted definition of a knowledge graph. Most definitions view the topic through a Semantic Web lens and include these features: [14] Flexible relations among knowledge in topical domains: A knowledge graph (i) defines abstract classes and relations of entities in a schema, (ii) mainly describes real world entities and their interrelations, organized in a graph ...
Snowflake schema used by example query. The example schema shown to the right is a snowflaked version of the star schema example provided in the star schema article. The following example query is the snowflake schema equivalent of the star schema example code which returns the total number of television units sold by brand and by country for 1997.
[5] [6] A relational database definition (database schema, sometimes referred to as a relational schema) can thus be thought of as a collection of named relation schemas. [7] [8] In implementations, the domain of each attribute is effectively a data type [9] and a named relation schema is effectively a relation variable (relvar for short).
For example, comparing attributes/skills (e.g., communication, analytical, IT skills) learnt across different university degrees (e.g., mathematics, economics, psychology) Venn diagram: Venn diagram: all possible logical relations between a finite collection of different sets.