Anne Tchounikine

Learn More
When changes occur on data organization, conventional multidimensional structures are not adapted because dimensions are supposed to be static. In many cases, especially when time covered by the data warehouse is large, dimensions of the hypercube must be redesigned in order to integrate evolutions. We propose an approach allowing to track history but also(More)
Data warehouses and OLAP systems help to interactively analyze huge volumes of data. Spatial OLAP refers to the integration of spatial data in multidimensional applications at the physical, logical and conceptual level. In order to include spatial information as a result of the decision-making process, we propose to define spatial measures as geographical(More)
Data warehouses store large volumes of data according to a multidimensional model with dimensions representing different axes of analysis. OLAP systems (online analytical processing) provide the ability to interactively explore the data warehouse. Rising volumes and complexity of data favor the use of more powerful distributed computing architectures.(More)