Fact Table
The centralized table in a star schema is called as FACT table. A fact table typically has two types of columns: those that contain facts
and those that are foreign keys to dimension tables.
The primary key of a fact table is usually a composite key that is made up of
all of its foreign keys.
In the example fig 1.6 "Sales Dollar" is a fact(measure) and it can be added across several dimensions. Fact tables store different types of measures like additive, non additive and semi additive measures.
- Measure Types
- Additive - Measures that can be added across all dimensions.
- Non Additive - Measures that cannot be added across all dimensions.
- Semi Additive - Measures that can be added across few dimensions and not with others.
A fact table might contain either detail level facts or facts that have been aggregated (fact tables that contain aggregated facts are often instead called summary tables).
In the real world, it is possible to have a fact table that contains no measures or facts. These tables are called as Factless Fact tables.
- Steps in designing Fact Table
- Identify a business process for analysis(like sales).
- Identify measures or facts (sales dollar).
- Identify dimensions for facts(product dimension, location dimension, time dimension, organization dimension).
- List the columns that describe each dimension.(region name, branch name, region name).
- Determine the lowest level of summary in a fact table(sales dollar).
Example of a Fact Table with an Additive Measure in Star Schema: Figure 1.6
In the example figure 1.6, sales fact table is connected to dimensions location, product, time and organization. Measure "Sales Dollar" in sales fact table can be added across all dimensions independently or in a combined manner which is explained below.
- Sales Dollar value for a particular product
- Sales Dollar value for a product in a location
- Sales Dollar value for a product in a year within a location
- Sales Dollar value for a product in a year within a location sold or serviced by an employee
RDBMS Database