Data Warehousing Tutorial

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Data Modeling Basics

Obtain key data modeling knowledge for your data warehousing project.

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

The Analytical Puzzle: Profitable Data Warehousing, Business Intelligence and Analytics
By David Haertzen