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If it takes too long to generate, you can limit the data by, for example, reducing the range of years.


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Interval OLAP: Analyzing Interval Data


[ 1 ] Instytut Informatyki, Wydział Informatyki, Politechnika Poznańska | [ P ] employee

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EN The ability to analyze data organized as sequences of events or intervals became important by nowadays applications since such data became ubiquitous. In this paper we propose a formal model and briefly discuss a prototypical implementation for processing interval data in an OLAP style. The fundamental constructs of the formal model include: events, intervals, sequences of intervals, dimensions, dimension hierarchies, a dimension members, and an iCube. The model supports: (1) defining multiple sets of intervals over sequential data, (2) defining measures computed from both, events and intervals, and (3) analyzing the measures in the context set up by dimensions.

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233 - 244





Data Warehousing and Knowledge Discovery : 16th International Conference, DaWaK 2014, Munich, Germany, September 2-4, 2014 : proceedings

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16th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2014, 2-4.09.2014, Munich, Germany

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