In Data Warehouse Modeling, a star schema and a snowflake schema consists of Fact and Dimension tables.
Fact Table:
It contains all the primary keys of the dimension and associated
facts or measures(is a property on which calculations can be made) like quantity sold, amount sold and average sales.
Dimension Tables:
Dimension tables provides descriptive information for all the measurements recorded in fact table.
Dimensions are relatively very small as comparison of fact table.
Commonly used dimensions are people, products, place and time.
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This appears to be a very simple answer on how to differentiate between fact and dimension tables!
It may help to think of dimensions as things or objects. A thing such
as a product can exist without ever being involved in a business
event. A dimension is your noun. It is something that can exist
independent of a business event, such as a sale. Products, employees,
equipment, are all things that exist. A dimension either does
something, or has something done to it.
Employees sell, customers buy. Employees and customers are examples of
dimensions, they do.
Products are sold, they are also dimensions as they have something
done to them.
Facts, are the verb. An entry in a fact table marks a discrete event
that happens to something from the dimension table. A product sale
would be recorded in a fact table. The event of the sale would be
noted by what product was sold, which employee sold it, and which
customer bought it. Product, Employee, and Customer are all dimensions
that describe the event, the sale.
In addition fact tables also typically have some kind of quantitative
data. The quantity sold, the price per item, total price, and so on.
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