Tables as a paradigm for querying and restructuring (extended abstract)
PODS '96 Proceedings of the fifteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
An overview of data warehousing and OLAP technology
ACM SIGMOD Record
A survey of logical models for OLAP databases
ACM SIGMOD Record
Discovery-Driven Exploration of OLAP Data Cubes
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Explaining Differences in Multidimensional Aggregates
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
A Foundation for Multi-dimensional Databases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Mining multiple-level fuzzy blocks from multidimensional data
Fuzzy Sets and Systems
A Multiple Correspondence Analysis to Organize Data Cubes
Proceedings of the 2007 conference on Databases and Information Systems IV: Selected Papers from the Seventh International Baltic Conference DB&IS'2006
Preference-Based Recommendations for OLAP Analysis
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
A Conceptual Modeling Approach for OLAP Personalization
ER '09 Proceedings of the 28th International Conference on Conceptual Modeling
Pixelizing data cubes: a block-based approach
VIEW'06 Proceedings of the 1st first visual information expert conference on Pixelization paradigm
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On-line analytical processing (OLAP) provides an interactive query-driven analysis of multidimensional data based on a set of navigational operators like roll-up or slice and dice. In most cases, the analyst is expected to use these operations intuitively to find interesting patterns in a huge amount of data of high dimensionality.In this paper, we propose an approach to enhance this analysis by preparing the data set so that the analyst can explore it in a more systematic and effective manner. More precisely we define a measurement of the quality of the representation of multidimensional data and we present a framework for investigating the computation of appropriate representations. We identify the problems of computing such representations and study them w.r.t. an OLAP restructuring operator.