Data warehousing and On-Line Analytical Processing (OLAP) are becoming critical components of decision support as advances in technology are improving the ability to manage and retrieve large volumes of data. Data warehousing refers to \a collection of decision support technologies aimed at enabling the knowledge worker (executive, manager, analyst) to make better and faster decisions" [1]. OLA...

Hierarchies are an important means to categorize data stored in OLAP systems. OLAP queries follow the drill/slice/dice-paradigm and therefore exhibit navigation patterns that follow the hierarchy of a dimension. In real-world applications, hierarchies are often unbalanced and share levels, resulting in complex hierarchy structures. So far, encoding methods for simple structured hierarchies have...

On-line analytical processing (OLAP) queries can take hours or even days to execute on very large data warehouses. Therefore, there is a need to employ techniques that can facilitate efficient execution of these queries. Data partitioning concept that has been studied in the context of relational databases aims to reduce query execution time and facilitate the parallel execution of queries. In ...

Hierarchies are used in data warehouses (DWs) and on-line analytical processing (OLAP) systems to see data at different levels of detail. However, many kinds of hierarchies arising in real-world situations are not addressed by current OLAP systems. Further, there is still no agreement on a conceptual model for DW and OLAP design that offers both a graphical representation and a formal definitio...

The historically introduced separation of online analytical processing (OLAP) from online transaction processing (OLTP) is in question considering the current developments of databases. Columnoriented databases mainly used in the OLAP environment so far, with the addition of in-memory data storage are adapted to accommodate OLTP as well, thus paving the way for mixed OLTP and OLAP processing. T...

DBPubs is a system for effectively analyzing and exploring the content of database publications by combining keyword search with OLAP-style aggregations, navigation, and reporting. DBPubs starts with keyword search over the content of publications. The publications’ metadata such as title, authors, venues, year, and so on, provide traditional OLAP static dimensions, which are combined with dyna...

The growing use of data analytics on Linked Data requires SPARQL engines to efficiently execute Online Analytical Processing (OLAP) queries. While SPARQL 1.1 provides appropriate basic constructs, corresponding optimization of SPARQL engines is still in its infancy and further development lacks benchmarks that mimick the data distributions found in Link Data. In fact, existing work on OLAP benc...

Résumé. Avec l’avènement de XML comme standard de représentation de données décisionnelles, les entrepôts de données XML trouvent leur place dans le développement de solutions décisionnelles basées sur le Web. Dans ce contexte, il devient nécessaire de permettre des analyses OLAP sur des cubes de données XML. Pour cela, des extensions du langage XQuery sont nécessaires. Afin de contribuer à ces...

The data warehouse should be refreshed periodically or aperiodically in order to prevent OLAP transactions from reading extremely stale data. This refreshing process is referred to as view maintenance. There have been many researches on ways to preserve data consistency during the process of view maintenance. The simplest approach among them is to perform view maintenance in the nighttime while...

Data warehousing and On-Line Analytical Processing (OLAP) are two of the most signiicant new technologies in the business data processing arena. A data warehouse can be deened as a \very large" repository of historical data pertaining to an organization. OLAP refers to the technique of performing complex analysis over the information stored in a data warehouse. The complexity of queries require...