: Integration of multiple data sources is becoming increasingly important for enterprises that cooperate closely with their partners for e-commerce. OLAP enables analysts and decis...
Navigating through multidimensional data cubes is a nontrivial task. Although On-Line Analytical Processing (OLAP) provides the capability to view multidimensional data through ro...
Navin Kumar, Aryya Gangopadhyay, George Karabatis,...
Multidimensional databases are now recognized as being the standard way to store aggregated and historized data. Multidimensional databases are designed to store information on me...
Online Analytical Processing is a powerful framework for the analysis of organizational data. OLAP is often supported by a logical structure known as a data cube, a multidimension...
Frank K. H. A. Dehne, Todd Eavis, Andrew Rau-Chapl...
Abstract. On Line Analytical Processing (OLAP) is a technology basically created to provide users with tools in order to explore and navigate into data cubes. Unfortunately, in hug...
Riadh Ben Messaoud, Omar Boussaid, Sabine Loudcher...
Efficiently answering decision support queries is an important problem. Most of the work in this direction has been in the context of the data cube. Queries are efficiently answer...
Jayavel Shanmugasundaram, Usama M. Fayyad, Paul S....
The normalization of a data cube is the process of choosing an ordering for the attribute values, and the chosen ordering will affect the physical storage of the cube’s data. For...
The data cube operator exemplifies two of the most important aspects of OLAP queries: aggregation and dimension hierarchies. In earlier work we presented Dwarf, a highly compress...
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...
On-line analytical processing (OLAP) provides tools to explore and navigate into data cubes in order to extract interesting information. Nevertheless, OLAP is not capable of expla...