Abstract
When utilising multidimensional OLAP (On-Line Analytic Processing) analysis models in Business Intelligence analysis, it is common that the users need to add new, unanticipated dimensions to the OLAP cube. In a conventional implementation, this would imply frequent re-designs of the cube’s dimensions. We present an alternative method for the addition of new dimensions. Interestingly, the same design method can also be used to import EAV (Entity-Attribute-Value) tables into a cube. EAV tables have earlier been used to represent extremely sparse data in applications such as biomedical databases. Though space-efficient, EAV-representation can be awkward to query.
Our EAV-to-OLAP cube methodology has an advantage of managing many-to-many relationships in a natural manner. Simple theoretical analysis shows that the methodology is efficient in space consumption. We demonstrate the efficiency of our approach in terms of the speed of OLAP cube re-processing when importing EAV-style data, comparing the performance of our cube design method with the performance of the conventional cube design.
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© 2011 Springer-Verlag Berlin Heidelberg
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Thanisch, P., Niemi, T., Niinimaki, M., Nummenmaa, J. (2011). Using the Entity-Attribute-Value Model for OLAP Cube Construction. In: Grabis, J., Kirikova, M. (eds) Perspectives in Business Informatics Research. BIR 2011. Lecture Notes in Business Information Processing, vol 90. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24511-4_5
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DOI: https://doi.org/10.1007/978-3-642-24511-4_5
Publisher Name: Springer, Berlin, Heidelberg
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