queries from that operational database because of the continuously updated transactions.Dimensionality Dimensionality is the most distinguishing characteristic of the DSS data. The data warehouse is set to provide the larger picture (2:64). In other words, it includes many data dimensions. For instance, a sale manager may ask how many units of product X were sold to customer Y during the last T months (2:66). So, he or she can view the data from three dimensions: product, customer and time. In fact, (s)he could view the data from many dimensions. This multidimensional view of the data is different from the single view of the operational database.HOW DOES DATA WAREHOUSE ASSIST IN DECISION-MAKINGIn order to gain the assistance of the data warehouse in the analysis and decision-making process, four main stages are required: storing the data, data extraction & filtering, query tools and presentation tools.Data StoreThe data store is a repository where the meta data (information about the data) are kept to describe the characteristics of the data in the DSS database. It is also linked with the transactional database so that any modification of the transactional data will be updated in the data warehouse as well. (2:65)Data Extraction & FilteringThe data warehouse contains two main types of data: data extracted from the production database and data from external sources (3:32) like stock price indicators. The data extraction & filtering tools are used to extract and validate the data taken from the transactional database and external data sources (3:32). The warehoused data are not the copy of the operational data. Instead, they are summarized and organized for analysis and query speed. Also, using data from external sources means having to solve data formatting conflicts (1:74). For example, when comparing the GPA (Grade Point Average) of two different universities say KFUPM and KFU (King Faisal University), many inconsistencies must be solv...
