The traditional databases are not capable of handling unstructured data and high volumes
of real-time datasets. Diverse datasets are unstructured lead to big data, and it is laborious …

Data Warehouses are the core of the modern systems for decision making. They store
integrated information extracted from various and heterogeneous data sources, making it …

This paper describes the convergence of some of the most influential technologies in the last
few years, namely data warehousing (DW), on-line analytical processing (OLAP), and the …

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 data warehouse design task needs to consider both the end-user requirements and the
organization data sources. For this reason, the data warehouse design has been …

Process mining techniques enable the analysis of processes using event data. For
structured processes without too many variations, it is possible to show a relative simple …

Many modern applications, including online financial feeds, tag-based mass transit systems
and RFID-based supply chain management systems transmit real-time data streams. There …

Exploratory OLAP aims at coupling the precision and detail of corporate data with the
information wealth of LOD. While some techniques to create, publish, and query RDF cubes …

At the early stages of a data warehouse design project, the main objective is to collect the
business requirements and needs, and translate them into an appropriate conceptual …