This short description of E-R models demonstrates them from the perspective of application types: OLTP (Online Transaction Processing) and DSS (Decision Support Systems). It also relates E-R notations to other notations.
The entity-relationship (E-R) model (of relational model) is the classic, fully normalized relational schema used in many online transaction processing (OLTP) systems. The relationships between entities (tables) signify relationships between data, not necessarily business relationships.
ER modeling technique was first developed by Peter Chen in 1976 to ensure:
The relational model of data prescribes how the data should be represented in terms of:
The rules of the relational model are widely accepted in the information technology industry, though actual implementations may vary.
With the growth of the machine power, this point of view is now not always true
Typically, E-R schemas have many tables, sometimes hundreds or even thousands. There are many tables because the data has been carefully taken apart—normalized, in database terminology—with the primary goal of:
E-R models are very efficient for OLTP databases. When E-R databases are queried, joins are usually predetermined and can be optimized. E-R databases are usually queried by applications that know exactly where to go and what to ask. These applications typically query small units of information at a time, such as a customer record, an order, or a shipment record.
E-R schemas generally do not work well for queries that perform historical analysis due to two major problems—poor performance and difficulty in posing the question in SQL:
The ERD is the most common technique for drawing data models.
The building blocks of the ERD are:
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