INFORMATION SYSTEMS IN MANAGEMENT IV

Gorawski [3], [4], [5]). Next we should design a logical structure of relations supportingthe data warehouse as a non-volatile source of data used for processingqueries. Moreover we should decide how to represent: tables, processes, indexes,and logical scheme of the data warehouse and how to ensure efficiency of thewhole system. We should also choose hardware and software for the given datawarehouse. Database schemes composing data warehouse may change because ofthe requirement changing possibility and therefore designing is a dynamic processin the life cycle of the system.There are two main approaches to storing data in a data warehouse: the dimensionaland the normalized approach.In the normalized approach data in the data warehouse are stored following databasenormalization rules. Tables are grouped together by subject areas that correspondto some data categories (e.g., data on customers, products, finance, etc.).Then we can get some difficulties with taking data from different sources and withjoining them into meaningful information and also with accessing informationwithout a precise understanding of the sources of data and of the data structure inthe data warehouse (because of the big number of tables involved). However thisapproach enables convenient adding information into the database.In the dimensional approach, transaction data are partitioned either into facts,which are usually numeric transaction data, or into dimensions, which are the referenceinformation that gives context to the facts. An example of facts is a salestransaction which can be broken up into such facts as the number of ordered productsand the price of these products. By dimension we mean a group of logicallyconnected attributes, e.g. day, month and year in the dimension date. As examplesof dimensions, we can distinguish customer name, product number, order date,order ship-to and bill-to locations, and name and address of salesperson responsiblefor receiving the order. A key advantage of a dimensional approach is that the datawarehouse is easier to understand and to use for users. The integrity of facts anddimensions are complicated and modelled enterprise should be stable because ofdifficulty to modify the data warehouse structure. However the retrieval of datafrom the data warehouse tends to operate very quickly. These approaches can bemixed and dimensional approaches can involve normalizing data to a degree.Another important question in designing a data warehouse is which data to conformand how to do this. For example, one operational system feeding data into thedata warehouse may use "M" and "F" to denote sex of an employee while anotheroperational system may use "Male" and "Female". During implementing a datawarehouse we should make consistent similar meaning data when they are stored inthe data warehouse. Usually extract, transform, load tools are used in such situations.There are two main data warehouse architectures: top-down (centralized) andbottom-up (distributed).49