Abstract
Accurate summarizability is an important property in OLAP systems because inaccurate summaries can result in poor decisions. Furthermore, it is important to understand and identify the potential sources of inaccurate summaries. In this paper, we present a taxonomy of inaccurate summary factors and practical rules for handling them. We consolidate relevant terms and concepts in statistical databases with those in OLAP systems and explore factors that are important for measuring the impact of erroneous summaries. We discuss these issues from the perspectives of schema, data, and computation. This paper contributes to a comprehensive understanding of summarizability and its impact on decision-making. Our work could help designers and users of OLAP systems reduce unnecessary constraints caused by imposing rules to eliminate all summarizability violations and give designers a means to prioritize problems.
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Horner, J., Song, IY. (2005). A Taxonomy of Inaccurate Summaries and Their Management in OLAP Systems. In: Delcambre, L., Kop, C., Mayr, H.C., Mylopoulos, J., Pastor, O. (eds) Conceptual Modeling – ER 2005. ER 2005. Lecture Notes in Computer Science, vol 3716. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11568322_28
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DOI: https://doi.org/10.1007/11568322_28
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