Using the entity-attribute-value model for olap cube construction
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Details
Original language | English |
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Title of host publication | Perspectives in Business Informatics Research - 10th International Conference, BIR 2011, Proceedings |
Publisher | Springer Verlag |
Pages | 59-72 |
Number of pages | 14 |
Volume | 90 LNBIP |
ISBN (Print) | 9783642245107 |
DOIs | |
Publication status | Published - 2011 |
Publication type | A4 Article in a conference publication |
Event | 10th International Conference on Perspectives in Business Informatics Research, BIR 2011 - Riga, Latvia Duration: 6 Oct 2011 → 8 Oct 2011 |
Publication series
Name | Lecture Notes in Business Information Processing |
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Volume | 90 LNBIP |
ISSN (Print) | 18651348 |
Conference
Conference | 10th International Conference on Perspectives in Business Informatics Research, BIR 2011 |
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Country | Latvia |
City | Riga |
Period | 6/10/11 → 8/10/11 |
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.
ASJC Scopus subject areas
Keywords
- dimensions, EAV, OLAP