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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.
It occurs when a (master) table links to multiple tables in a one-to-many relationship. The issue derives its name from the visual appearance of the model when it is drawn in an entity–relationship diagram, as the linked tables 'fan out' from the master table. This type of model resembles a star schema, which is a common design in data ...
Entity relationship diagram (ERD) notations [ edit ] One notation as described in Entity Relationship modeling is Chen notation or formally Chen ERD notation created originally by Peter Chen in 1976 where a one-to-many relationship is notated as 1:N where N represents the cardinality and can be 0 or higher.
The last step in data modeling is transforming the logical data model to a physical data model that organizes the data into tables, and accounts for access, performance and storage details. Data modeling defines not just data elements, but also their structures and the relationships between them.
Barker's notation refers to the ERD notation developed by Richard Barker, Ian Palmer, Harry Ellis et al. whilst working at the British consulting firm CACI around 1981. The notation was adopted by Barker when he joined Oracle and is effectively defined in his book Entity Relationship Modelling as part of the CASE Method series of books.
Overview of a data-modeling context: Data model is based on Data, Data relationship, Data semantic and Data constraint. A data model provides the details of information to be stored, and is of primary use when the final product is the generation of computer software code for an application or the preparation of a functional specification to aid a computer software make-or-buy decision.
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Normalization splits up data to avoid redundancy (duplication) by moving commonly repeating groups of data into new tables. Normalization therefore tends to increase the number of tables that need to be joined in order to perform a given query, but reduces the space required to hold the data and the number of places where it needs to be updated if the data changes.