: Data warehousing and Online Analytical Processing (OLAP) technologies are now moving onto handling complex data that mostly originate from the web. However, integrating such data...
: In a data warehousing process, the phase of data integration is crucial. Many methods for data integration have been published in the literature. However, with the development of...
The gap between researchers and practitioners is widely discussed in the IT community. The purpose of this paper is towards showing the issues which occupy both research and pract...
Data warehousing is a software infrastructure which supports OLAP applications by providing a collection of tools which allow data extraction and cleaning, data integration and ag...
The need for an integrated enterprise-wide set of management information pronounced Data Warehousing the `hot topic' of the early-to-mid 1990's, however, it became unfas...
The importance of metadata has been broadly referred in the last years, mainly in the field of data warehousing and decision support systems. Contemporarily, in the adjacent field...
The DWS (Data Warehouse Striping) technique is a data partitioning approach especially designed for distributed data warehousing environments. In DWS the fact tables are distribute...
Raquel Almeida, Jorge Vieira, Marco Vieira, Henriq...
A well-known challenge in data warehousing is the efficient incremental maintenance of warehouse data in the presence of source data updates. In this paper, we identify several cr...
Wilburt Labio, Jun Yang 0001, Yingwei Cui, Hector ...
The topic of data warehousing encompasses architectures, algorithms, and tools for bringing together selected data from multiple databases or other information sources into a sing...
Data warehousing involves complex processes that transform source data through several stages to deliver suitable information ready to be analysed. Though many techniques for visua...