In recent years, facing information explosion, industry and academia have adopted distributed file system and MapReduce programming model to address new challenges the big data has brought. Based on these technologies, this paper presents HaoLap (Hadoop based oLap), an OLAP (OnLine Analytical Processing) system for big data. Drawing on the experience of Multidimensional OLAP (MOLAP), HaoLap ado...

Although the integration of data mining and OLAP is obviously of great interest (if only due to the widespread availability of commercial-strength OLAP tools), relatively little progress has been made in this integration. The main goal of this paper is to contribute to this integration, by incorporating some data mining functionality (more precisely, deviation-detection functionality) into the ...

On-Line Analytical Processing (OLAP) is a trend in database technology, based on the multidimensional view of data. In this paper we introduce the Cube Presentation Model (CPM), a presentational model for OLAP data which, to the best of our knowledge, is the only formal presentational model for OLAP found in the literature until today. First, our proposal extends a previous logical model for cu...

Online Analytical Processing (OLAP) promises an interface to analyse Linked Data containing statistics going beyond other interaction paradigms such as follow-your-nose browsers, faceted-search interfaces and query builders. Transforming statistical Linked Data into a star schema to populate a relational database and applying a common OLAP engine do not allow to optimise OLAP queries on RDF or ...

L’analyse en ligne OLAP (On Line Analytical Processing) soutient les entrepôts de données dans le processus d’aide à la décision. Cependant, il n’existe pas d’outils pour guider l’utilisateur dans l’exploration, ni pour approfondir l’analyse vers l’explication et la prédiction. Dans un processus décisionnel, un utilisateur peut vouloir anticiper la réalisation d’évènements futurs. Le couplage d...

Data Warehouses (DW) and OnLine Analytical Processing (OLAP) tools are used in Business Intelligence (BI) applications in order to support decision-making processes. DWs are a specific type of database used to integrate, accumulate and analyze data from various sources. OLAP tools provide means to query and to analyze the warehoused information and produce online statistical summaries (indicato...

During the last few years, On-Line Analytical Processing (OLAP) has emerged as a valuable tool for the analysis, navigation and reporting of hierarchically organized data from data warehouses. It particularly gained popularity as a building block of modern decision-support systems. With the use of geographical information systems in conjunction with OLAP, the need for storing spatial data and p...

Inspired by pointfree relational data processing, this paper addresses the foundations of an alternative roadmap for parallel online analytical processing (OLAP) based on a separation of concerns: rather than depending on standard database technology and heavy machinery, OLAP operations are performed by encoding data in matrix format and relying thereupon solely on LA operations. The paper inve...

The number of On-Line Analytical Processing (OLAP) applications in the market has dramatically increased in the last years. Most of these applications provide their own multidimensional (MD) models to represent main MD properties, thereby making the design totally dependent of the target commercial OLAP application. In this paper, we present a Computer-Aided SoftwareEngineering (CASE) operation...

OLAP queries involve a lot of aggregations on a large amount of data in data warehouses. To process expensive OLAP queries efficiently, we propose a new method to rewrite a given OLAP query using various kinds of materialized views which already exist in data warehouses. We first define the normal forms of OLAP queries and materialized views based on the selection and aggregation granularities,...