A data mart (or star schema) seems redundant and a waste of hard disk space. Why can I just use my operational data without also storing it in a data mart?
A. The fact is that the best reporting solutions require some amount of redundant data. In addition, OLTP systems have inherent problems that severely limit their effectiveness as for business intelligence: • OLTP data can be very inconsistent. For example, customer name fields may be formatted as last name, first name & middle initial in one table, as first name, middle initial & last name in another table, or contained all in one field in another table. Cleansing the data prior to loading it into a data warehouse can remove many of these inconsistencies. • OLTP data typically changes frequently. For example, the number of available units of a particular product can change very rapidly in the course of an hour. An analysis of the number of units sold could vary greatly from one analysis to the next. Refreshing the data in a data warehouse can be scheduled so that the data used for analysis is relatively constant. • The data might be located in multiple data sources. Data warehouses pr
