Logical Data Modeling - Attribute

1 - About

An attribute is a property or characteristic of a primary element (entity, relationship)

An attribute is just a shortcut for an entity that has only one characteristic and a one-to-one relationship with its entity.
For example, a color attribute could have been modeled also as an entity with several attributes (warm, cold, …)

The values for each attribute are defined in terms of properties.

An attribute is known as a:

  • field in object
  • variable in pure code
  • column metadata - in a relational model
  • variable metadata - in statistic

3 - Functionality

4 - Properties

Each attribute are defined in terms of properties (metadata attributes):

  • Name:
    • It provides a semantic meaning for the values.
    • the name of the attribute may contain a prefix of its element
  • Description
  • Attribute Source Category:
  • Data type (what class of data can be stored in that attribute)
  • Length and/or precision
  • Domain: enumeration, range of permitted, legal values / Format patterns (what values an attribute can legitimately take on)
  • Default value or algorithm (what default value are recorded if not specified by the user)
  • Optionality: Mandatory or optional
  • analytical property - descriptive or measure

4.1 - Attribute Source Categories

4.1.1 - Basic

An Attribute Value that cannot be deduced or calculated. Examples:

  • Student name
  • Birthday

4.1.2 - Derived / Calculated

4.1.3 - Designed

The Attribute is created to overcome the system constraints. The value of a Designed Attribute does not change. Attribute does not change.

Examples:

  • Student ID,
  • Course number.

Data Science
Data Analysis
Statistics
Data Science
Linear Algebra Mathematics
Trigonometry

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