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Incomplete Information in Multidimensional Databases

Incomplete Information in Multidimensional Databases

Cirtis E. Dyreson, Torben Bach Pedersen, Christian S. Jensen
Copyright: © 2003 |Pages: 28
ISBN13: 9781591400530|ISBN10: 1591400538|EISBN13: 9781591400868
DOI: 10.4018/978-1-59140-053-0.ch010
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MLA

Dyreson, Cirtis E., et al. "Incomplete Information in Multidimensional Databases." Multidimensional Databases: Problems and Solutions, edited by Maurizio Rafanelli, IGI Global, 2003, pp. 282-309. https://doi.org/10.4018/978-1-59140-053-0.ch010

APA

Dyreson, C. E., Pedersen, T. B., & Jensen, C. S. (2003). Incomplete Information in Multidimensional Databases. In M. Rafanelli (Ed.), Multidimensional Databases: Problems and Solutions (pp. 282-309). IGI Global. https://doi.org/10.4018/978-1-59140-053-0.ch010

Chicago

Dyreson, Cirtis E., Torben Bach Pedersen, and Christian S. Jensen. "Incomplete Information in Multidimensional Databases." In Multidimensional Databases: Problems and Solutions, edited by Maurizio Rafanelli, 282-309. Hershey, PA: IGI Global, 2003. https://doi.org/10.4018/978-1-59140-053-0.ch010

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Abstract

While incomplete information is endemic to real-world data, current multidimensional data models are not engineered to manage incomplete information in base data, derived data, and dimensions. This chapter presents several strategies for managing incomplete information in multidimensional databases. Which strategy to use is dependent on the kind of incomplete information present, and also on where it occurs in the multidimensional database. A relatively simple strategy is to replace incomplete information with appropriate, complete information. The advantage of this strategy is that all multidimensional databases can manage complete information. Other strategies require more substantial changes to the multidimensional database. One strategy is to reflect the incompleteness in computed aggregates, which is possible only if the multidimensional database allows incomplete values in its hierarchies. Another strategy is to measure the amount of incompleteness in aggregated values by tallying how much uncertain information went into their production.

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