Extending visual OLAP for handling irregular dimensional hierarchies


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MANSMANN, Svetlana, Marc H. SCHOLL, 2006. Extending visual OLAP for handling irregular dimensional hierarchies. DaWaK. Krakow, Poland, 4. Sep 2006 - 8. Sep 2006. In: TJOA, A Min, ed., Juan TRUJILLO, ed.. Data warehousing and knowledge discovery : 8th international conference. Berlin [u.a.]:Springer, pp. 95-105. ISBN 978-3-540-37736-8. Available under: doi: 10.1007/11823728

@inproceedings{Mansmann2006Exten-17628, title={Extending visual OLAP for handling irregular dimensional hierarchies}, year={2006}, doi={10.1007/11823728}, number={4081}, isbn={978-3-540-37736-8}, address={Berlin [u.a.]}, publisher={Springer}, series={Lecture notes in computer science}, booktitle={Data warehousing and knowledge discovery : 8th international conference}, pages={95--105}, editor={Tjoa, A Min and Trujillo, Juan}, author={Mansmann, Svetlana and Scholl, Marc H.} }

2012-02-01T09:20:24Z 2012-02-01T09:20:24Z Mansmann, Svetlana 2006 Extending visual OLAP for handling irregular dimensional hierarchies Mansmann, Svetlana Scholl, Marc H. terms-of-use eng Publ. in: Data warehousing and knowledge discovery : 8th international conference, DaWaK 2006, Krakow, Poland, September 4 - 8, 2006 ; proceedings ; [held at DEXA 06] / A Min Tjoa; Juan Trujillo (eds.). Berlin [u.a.] : Springer, 2006. S. 95-105. - ( Lecture notes in computer science ; 4081 ). - ISBN 978-3-540-37736-8 Comprehensive data analysis has become indispensable in a variety of environments. Standard OLAP (On-Line Analytical Processing) systems, designed for satisfying the reporting needs of the business, tend to perform poorly or even fail when applied in non-business domains such as medicine, science, or government. The underlying multidimensional data model is restricted to aggregating only over summarizable data, i.e. where each dimensional hierarchy is a balanced tree. This limitation, obviously too rigid for a number of applications, has to be overcome in order to provide adequate OLAP support for novel domains.<br /><br />We present a framework for querying complex multidimensional data, with the major effort at the conceptual level as to transform irregular hierarchies to make them navigable in a uniform manner. We provide a classification of various behaviors in dimensional hierarchies, followed by our two-phase modeling method that proceeds by eliminating irregularities in the data with subsequent transformation of a complex hierarchical schema into a set of well-behaved sub-dimensions.<br /><br />Mapping of the data to a visual OLAP browser relies solely on metadata which captures the properties of facts and dimensions as well as the relationships across dimensional levels. Visual navigation is schemabased, i.e., users interact with dimensional levels and the data instances are displayed on-demand. The power of our approach is exemplified using a real-world study from the domain of academic administration. Scholl, Marc H.

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