In data warehousing, a
Fact table consists of the measurements, metrics or facts of a business
process. It is located at the center of a star schema or a snowflake schema
surrounded by dimension tables. Where multiple fact tables are used, these are
arranged as a fact constellation schema. A fact table typically has two types
of columns: those that contain facts and those that are a foreign key 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. Fact tables contain the content of the data
warehouse and store different types of measures like additive, non additive,
and semi additive measures.
Fact tables provide
the (usually) additive values that act as independent variables by which
dimensional attributes are analyzed. Fact tables are often defined by their
grain. The grain of a fact table represents the most atomic level by which the
facts may be defined. The grain of a SALES fact table might be stated as
"Sales volume by Day by Product by Store". Each record in this fact
table is therefore uniquely defined by a day, product and store. Other
dimensions might be members of this fact table (such as location/region) but
these add nothing to the uniqueness of the fact records. These "affiliate
dimensions" allow for additional slices of the independent facts but
generally provide insights at a higher level of aggregation (a region contains
many stores).
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