Data Warehousing and Business Intelligence at the Data Management Center 

Data Warehousing Tutorial

Learn Data Warehousing and Business Intelligence.
Jump start your data warehousing efforts.
Bookmark and Share

 

Data Modeling Basics

Obtain key data modeling knowledge for your data warehousing project.

David Haertzen David Haertzen, Principal Enterprise Architect


Data models whether used for data warehousing or other purposes tend to be designed using commonly understood symbols and terminologies. This section will provide you with that grounding.

There are three levels of data modeling:

  • Conceptual Data Model - a high level model that describes a problem.
  • Logical Data Model - a detailed data model that describes a solution using business terms.
  • Physical Data Model - a detailed data model that defines database objects. This model is needed to implement the models in a database and produce a working solution.

An entity is an object of interest to the enterprise. An entity can be a: lperson, lorganization, lplace, lthing, lactivity, levent, labstraction or idea.  Entities are represented as rectangles in the data model:

Data Model Entity

An attribute is a characteristic of an entity.  It may contain data values, for example:
  • order number
  • account balance amount
  • marital status code
  • item description
  • skill level code

A relationship is an association between entities.  Relationships are expressed as verbs or verb phrases.  Data modeling focuses on binary relationships for example:

lcustomer  places   order
lregion contains district
lemployee has developed skill
lsales representative is responsible for territory
 
Data Model - Relationship