Defining data warehouse requirements is widely recognized as one of the most important steps in the larger data warehouse system development process. This paper examines the potential risks and pitfalls within the data warehouse requirement collection and definition process. A real scenario of a large-scale data warehouse implementation is given, and details of this project, which ultimately fa...

Metadata represents the information about data to be stored in Data Warehouses. It is a mandatory element of Data Warehouse to build an efficient Data Warehouse. Metadata helps in data integration, lineage, data quality and populating transformed data into data warehouse. Spatial data warehouses are based on spatial data mostly collected from Geographical Information Systems (GIS) and the trans...

Mediators are a critical component of any data warehouse; they transform data from source formats to the warehouse representation while resolving semantic and syntactic conflicts. The close relationship between mediators and databases requires a mediator to be updated whenever an associated schema is modified. Failure to quickly perform these updates significantly reduces the reliability of the...

Despite the increasing role of the data warehouse as a strategic information source for decision makers, academic research has been lacking, especially from an organizational perspective. An exploratory study was conducted to improve general understanding of data warehousing issues from the perspective of IS success. For this, the effect of variables pertaining to system quality, information qu...

Data warehouse systems are used by decision makers for performance measurement and decision support. Measures such as the number of transactions per customer or the increase of sales during a promotion are used to recognize warning signs and to decide on future investments with regard to the strategic goals of the organization. Currently, the main focus of the data warehouse research field is o...

Data warehouse is a collection of huge database which is subject oriented, integrated, time-variant and non volatile. As it is a set of huge database, fast data access is the major performance parameter of any data warehouse. Generally the information retrieved from Data Warehouse is summarized or aggregated as it is required for some decision making process of organization. To retrieve such a ...

Data warehouse is considered as the core component of the modern decision support systems. Due to the major support of data warehouse in the daily transaction of an enterprise, the requirements for the design and the implementation of DW are dynamic and subjective. This dynamic nature of the data warehouse may reflect the evolution in the data warehouse. Data warehouse evolution may be focused ...

Traditional enterprise data warehouse, an integral part of decision support systems (DSS), provides a variety of granularity data to satisfy requirements of different users. It is estimated that about 80% of the information stored in data warehouse is geo-spatial related. However, traditional data warehouse cannot efficiently process spatial data. With the increasing amount of spatial data stor...

the bi-objective warehouse problem in a crisp environment is often not eective in dealing with the imprecision or vagueness in the values of the problem parameters. to deal with such situations, several researchers have proposed that the parameters be represented as fuzzy numbers. we describe a new algorithm for fuzzy bi-objective warehouse problem using a ranking function followed by an applic...

With the emergence of data warehousing, Decision Support Systems have evolved to its best. At the core of these warehousing systems lies a good database management system. Database server, used for data warehousing, is responsible to provide robust data management, scalability, high performance query processing and integration with other servers. Oracle being the initiator in warehousing server...