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OLAP (On-line Analytical Processing) technologies rely on multidimensional models to provide decision makers with appropriate structures allowing them to intuitively analyze data. However, these multidimensional models may be potentially large, thus becoming too complex to be understood at a glance. Current approaches for OLAP design are focused on providing analysts with a single multidimensional schema derived from their previously stated information requirements, but this is not sufficient to lighten the complexity of the decision making process. To overcome this drawback, the authors propose personalizing multidimensional models for OLAP technologies according to the continuously changing user characteristics, context, requirements and behavior. In this paper, they present a new approach for personalizing OLAP systems at the conceptual level based on the underlying multidimensional model, a user model and a set of personalization rules. Transformations are defined by means of a model-driven strategy to assist in the process of obtaining the corresponding personalized OLAP schemas from these models. Keywords: Conceptual modeling, Model-Driven Strategy, Multidimensional Modeling, On-line Analytical Processing (OLAP), Personalization, INTRODUCTION Current approaches for OLAP start by defining a multidimensional model (Rizzi, Abello. Lechtenborger, & Trujillo, 2006) in order to obtain a unified view with which all decision makers intuitively [...]

To customize a data warehouse, many organizations develop concrete data marts focused on a particular department or business process. However, the integrated development of these data marts is an open problem for many organizations due to the technical and organizational challenges involved during the design of these repositories as a complete solution. In this article, the authors present a design approach that employs user requirements to build both corporate data warehouses and data marts in an integrated manner. The approach links information requirements to specific data marts elicited by using goal-oriented requirement engineering, which are automatically translated into the implementation of corresponding data repositories by means of model-driven engineering techniques. The authors provide two UML profiles that integrate the design of both data warehouses and data marts and a set of QVT transformations with which to automate this process. The advantage of this approach is that user requirements are captured from the early development stages of a data-warehousing project to automatically translate them into the entire data-warehousing platform, considering the different data marts. Finally, the authors provide screenshots of the CASE tools that support the approach, and a case study to show its benefits. Keywords: Conceptual Modeling, Customization, DataMart, Data Warehouse, Goal-Oriented Requirement Engineering, MDA, Model-Driven Engineering, QVT, INTRODUCTION A corporate data warehouse is a repository that provides decision makers with a large amount of historical data concerning the overall enterprise strategy. A data-warehousing architecture defines a set [...]

ABSTRACT Several approaches have been proposed to model different aspects of a Data Warehouse (DW) during recent years, such as the modeling of a DW at the conceptual and logical […]

ABSTRACT Multidimensional (MD) modeling is the basis for data warehouses (DW), multidimensional databases (MDB) and on-line analytical processing (OLAP) applications. In this paper, we present how the unified modeling language […]

The huge amount of information available and its heterogeneity has surpassed the capacity of current data management technologies. Dealing with huge amounts of structured and unstructured data, often referred as Big Data, is a hot research topic and a technological challenge. In this paper, the authors present an approach aimed to enable OLAP queries over different, heterogeneous, data sources. Their approach is based on a MapReduce paradigm, which integrates different formats into the recent RDF Data Cube format. The benefits of their approach are that it is capable of querying different sources of information, while maintaining at the same time, an integrated, comprehensive view of the data available. The paper discusses the advantages and disadvantages, as well as the implementation challenges that such approach presents. Furthermore, the approach is evaluated in detail by means of a case study., Author(s): Alejandro Maté, Department of Software and Computing Systems, University of Alicante, Alicante, Spain, Hector Llorens, Department of Software and Computing Systems, University of Alicante, Alicante, Spain, Elisa de Gregorio, [...]