Logical data modeling is a graphic-intensive technique that results in a data model representing the definition, characteristics, and relationships of data in a business, technical, or conceptual environment. Various methods of data modeling exist, each using a host of conventions and tools. Although a number of authors and tool designers have modified and expanded ER concepts, most still have a strong Chen flavor. Also, with the introduction of CASE tools, the number of diagrammatic conventions that the data modeler must master has increased sharply. Employees, States, Orders, and Time Sheets are examples of entities.
Attributes are the properties of entities.
Attribute examples include Color, Employment Date, Name, and Social Security Number. Relationship entity pairs are bidirectional. While a number of graphical conventions represent data objects, one convention on which all the different approaches seem to agree is the use of a rectangular box to represent an entity. Relationships are represented by a line. However, for various reasons, including time, space, and laziness, modelers often do not label relationships in both directions.