The data warehousing and OLAP technologies are now moving onto handling complex data that mostly originate from the Web. However, intagrating such data into a decision-support process requires their representation under a form processable by OLAP and/or data mining techniques. We present in this paper a complex data warehousing methodology that exploits XML as a pivot language. Our approach inc...

In this paper we present the SQL OLAP data model, formal algebra, and query language that, unlike current OLAP data models and languages, are both powerful, meaning that they support irregular dimension hierarchies, automatic aggregation of data, and correct aggregation of data, and SQL-compatible, allowing seamless integration with relational technology. We also consider the requirements to th...

Widely used in decision support systems, OLAP (Online Analytical Processing) technology facilitates interactive analysis of multi-dimensional data of varied granularities. In this paper, we demonstrate an interesting application of OLAP in solving multicriteria maintenance scheduling problems. Maintenance scheduling has many important applications, such as maintenance of inverted indexes for se...

Histograms are an important tool for data reduction both in the field of data-stream querying and in OLAP, since they allow us to represent large amount of data in a very compact structure, on which both efficient mining techniques and OLAP queries can be executed. Significant timeand memory-cost advantages may derive from data reduction, but the trade-off with the accuracy has to be managed in...

A Data Warehouse is a centralized repository of data acquired from external data sources and organized following a multidimensional model (Inmon, 1996) in order to be analyzed by On-Line Analytical Processing (OLAP) applications. OLAP tools provide the ability to interactively explore multidimensional data presenting detailed and aggregated data. The results of analyses are the basis of strateg...

Online analytical processing (OLAP) as a modern business intelligence (BI) concept provides support for representing vast amounts of data for supporting management " s decisions. Though, there is no inherent support for the representation of causal structures which could provide a foundation for advanced analysis like what-if or scenario techniques. System Dynamics (SD) is an approach with a lo...

The data collected by medical and healthcare industry is not turned into useful information for effective decision making. Advanced technologies such as OnLine Analytical Processing (OLAP) and data mining can be used by the Decision support systems (DSS) to deliver advanced capabilities. This paper presents a decision support system which combines the strengths of both OLAP and data mining. The...