An important aspect of data warehousing is the FACT table. A fact table basically represents the measurements, metrics, or FACTS of a business process. In fact tables, facts are stored, and they are linked to a number of dimension tables via foreign keys. Facts are usually details and/or aggregated measurements of a business process which can be calculated and grouped to address the business question. Data schemas LIKE the star schema or snowflake schema consist of a central fact table surrounded by several dimension tables. The measures or numbers like sales, cost, profit and loss, etc., are some examples of facts. 

Fact tables have two types of columns, foreign keys and measures columns. Foreign keys store foreign keys to dimensions, while measures contain NUMERIC facts. Other attributes can be added, depending on the business need and necessity. 

Types of Facts 

Facts can be divided into three basic types, as follows: 

• Additive: Facts that are fully additive are the most flexible and useful. We can sum up additive facts ACROSS any dimension associated with the fact table.
• Semi-additive: We can sum up semi-additive facts across some dimensions associated with the fact table, but not all.
• Non-Additive: The Fact table contains non-additive facts, which cannot be summed up for any dimension. The ratio is an example of a non-additive fact.