MS.11 Multidimensional Data Modeling for Cloud Intelligence

Cloud intelligence emerges from the migration of BI and analytics technologies to a cloud computing environment while exploiting the associated new opportunities. A multitude of different types of data exist "in the cloud," including structured, relational data, multidimensional cube data, text data, semantic web XML/RDF/OWL data, geo-related data, and sensor data. Finally, many analytical models of data have been developed through data mining. To achieve true cloud intelligence, all these types of data/models must be integrated and analyzed in a coherent fashion, including privacy protection, in a common "cloud warehouse" (CW). As a basis for the CW, this topic will develop a novel data model that combines the powerful analytical concepts from multidimensional data models, the flexibility from Semantic Web data models, and support for the wide range of data and functionality mentioned above. The project will further develop an equally powerful query language for the model, implement the functionality on a suitable cloud platform, and consider query optimizations.

Main Advisor at Aalborg Universitet (AAU)
Co‐advisor at Universitat Politècnica de Catalunya (UPC)