Dimensional Data Modeling - Descriptif Attribute (Dimensional Attribute)

1 - About

A descriptif attribute is class attribute that describe a property or characteristic of a dimension.

They are used to label, filter and/or group on.

whereas measures are attribute to aggregate over

3 - Example

Typical attributes for a product dimension :

  • short description (10 to 15 characters)
  • long description (30 to 50 characters)
  • a brand name
  • packaging type
  • size (It's a number but it behaves more like a textual descriptor, Size is a discrete and constant descriptor of a specific product)
  • square footage in store dimension. One might be tempted to place it in the fact table. However, it's clearly a constant attribute of a store and is used as report filter.
  • numerous other product characteristic.

4 - Naming

  • The best attributes are discrete (textual)
  • They should consist of real words rather than cryptic abbreviations.

5 - Identification

In a query or a report request, this descriptive attributes are identified by:

  • the by words.
  • and where words

For example, when a user states that he or she wants to see dollar sales by week by brand, week and brand must be available as dimension attributes.

6 - Data Type

The data type is generally discrete but not always. You may find numeric descriptif attribute.

For example: the revenue of last year is a descriptif element even if it's a number because you may want to use it as a filter to retain customers with a certain amount of revenue.

Generally, numeric attribute would have gone through a binning process to transform them as discrete (ie from revenue to top / middle / law revenue customer)

7 - Sql

They serve as the primary source for:

  • filtering,
  • grouping
  • and reporting labels.

The descriptif attributes are used in the following SQL statement:

They are not used in any aggregate function.

8 - Grain

The combination of all level of each descriptif attributes forms the grain of a relation (table, query,…).


Data Science
Data Analysis
Statistics
Data Science
Linear Algebra Mathematics
Trigonometry

Powered by ComboStrap