By Elzbieta Malinowski
This unprecedented paintings presents readers with an advent to the state of the art study on facts warehouse layout, with many references to extra specified resources. It deals a transparent and a concise presentation of the key suggestions and ends up in the topic quarter. Malinowski and Zim?nyi clarify traditional info warehouse layout intimately, and also deal with leading edge domain names lately brought to increase the features of knowledge warehouse platforms: specifically, the administration of spatial and temporal details.
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Additional resources for Advanced Data Warehouse Design: From Conventional to Spatial and Temporal Applications (Data-Centric Systems and Applications)
Further, the attributes composing the primary key do not accept null values. Referential integrity allows links between two tables (or twice the same table) to be speciﬁed, where a set of attributes in one table, called the foreign key, references the primary key of the other table. This means that the values accepted in the foreign key must also exist in the primary key. In Fig. 2, referential integrity constraints are represented by arrows from the foreign key to the primary key of the table that is referenced.
The development of conventional, spatial, and temporal data warehouses is a very complex task that requires several phases for its realization. It is therefore necessary to specify a method in order to assist developers in the execution of these phases. Existing methods oﬀer a variety of solutions, especially for the requirements speciﬁcation phase. However, such a diversity of approaches can be confusing for designers. For example, one approach ﬁrst considers users’ requirements and then checks them against the availability of data in the source systems, while another approach ﬁrst develops the data 1 We ignore modiﬁcations due to errors during data loading, and deletions for purging data in data warehouses.
This may lead to a situation where the data warehouse may not meet users’ expectations for supporting the decision-making process. In addition, some of the existing proposals include additional phases corresponding to particular characteristics of the conceptual multidimensional model in use. In this way, these methods impose on designers a conceptual model that may be unknown to them and may also be inadequate for a particular data warehouse project. Moreover, even though many organizations may require a data warehouse for the purpose of enhancing their decision-making processes, they might not be able to aﬀord external teams or consultants to build it.