Data warehouse systems integrate data from heterogeneous sources. These sources are autonomous in nature and change independently of a data warehouse. Owing to changes in data sources, the content and the schema of a data warehouse may need to be changed for accurate decision making. Slowly changing dimensions and temporal data warehouses are the available solutions to manage changes in the con...

Warehouse is one of the important aspects of a company. Therefore, it is necessary to improve Warehouse Management System (WMS) to have a simple function that can determine the layout of the storage goods. In this paper we propose an improved warehouse layout method based on ant colony algorithm and backtracking algorithm. The method works on two steps. First, it generates a solutions parameter...

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 is one of the most rapidly growing areas in management information systems. With this approach, data for EIS and DSS applications is separated from operational data and stored in a separate database called a data warehouse. Some of the advantages of this approach are improved performance, better data quality, and the ability to consolidate and summarize data from heterogeneous le...

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 ...