Data is the lifeblood of any organization. In today's world, organizations recognize the vital
role of data in modern business intelligence systems for making meaningful decisions and …

Since the late 1970s, relational database technology has been adopted by most
organizations to store their essential data. However, nowadays, the needs of these …

Data, information and knowledge have important role in various human activities because
by processing data, information is extracted and by analyzing data and information the …

A data warehouse stores large volumes of historical data required for analytical purposes.
This data is extracted from operational databases; transformed into a coherent whole using …

Materialized views are queries whose results are stored and maintained in order to facilitate
access to data in their underlying base tables. In the SQL setting, they are now considered a …

Data about the Earth, like in many other domains, are too difficult to access. In order to
perform some insight-gaining task a series of steps has to be performed which often require …

The Semantic Web (SW) deployment is now a realization and the amount of semantic
annotations is ever increasing thanks to several initiatives that promote a change in the …

The development of a data warehouse (DW) system is based on a conceptual
multidimensional model, which provides a high level of abstraction in accurately and …

We extend the OLAP data model to represent data ambiguity, specifically imprecision and
uncertainty, and introduce an allocation-based approach to the semantics of aggregation …

Traditional OLAP tools have proven to be successful in analyzing large sets of enterprise
data. For today's business dynamics, sometimes these highly curated data is not enough …