The data sources may include operational databases as well as spreadsheets and legacy systems. Any details in the data sources irrelevant to the analysis needs should be removed. For example, the phone number and street address of a store are probably not of interest, but its city probably is. We must also ensure that all facts of the same type are represented in the same way. As a trivial example, a customer's birthdate might be recorded as a character string in a 'DOB' field in one source, and elsewhere in a 'birthdate' column based on a date data type.
Employee manages Store.
Over time, a store may have different managers. Temporal modeling in general is an interesting topic, but a full treatment of it is beyond the scope of this book. As a simple example of derived data, suppose an operational source stores the fact type Customer was born on Date. For demographical analysis, we may be interested in how product preferences are influenced by the age of customers. The snapshot dates are inserted when the fact type is incrementally updated.