Parallelism can be used for major performance improvement in large Data warehouses (DW) with performance and scalability challenges. A simple low-cost shared-nothing architecture ...
BST Condensed Cube is a fully computed cube that condenses those tuples, which are aggregated from the same single base relation tuple, into one physical tuple. Although it has be...
A peer-to-peer (P2P) data management system consists essentially of a network of peer systems, each maintaining full autonomy over its own data resources. Data exchange between pe...
We address the inference control problem in data cubes with some data known to users through external knowledge. The goal of inference controls is to prevent exact values of sensi...
In today’s OLAP systems, integrating fast changing data, e.g., stock quotes, physically into a cube is complex and time-consuming. The widespread use of XML makes it very possib...
Computer system sizing involves estimating the amount of hardware resources needed to support a new workload not yet deployed in a production environment. In order to determine th...
Ted J. Wasserman, Patrick Martin, David B. Skillic...
CRM is a strategy that integrates the concepts of Knowledge Management, Data Mining, and Data Warehousing in order to support the organization’s decision-making process to retai...
The DWS (Data Warehouse Striping) technique allows the distribution of large data warehouses through a cluster of computers. The data partitioning approach partition the facts tab...
During the few last years, several approaches have been proposed to model different aspects of a Data Warehouse (DW), such as the conceptual model of the DW, the design of the ET...