DocumentCode :
2259813
Title :
Summarizability in OLAP and statistical data bases
Author :
Lenz, Hans-J ; Shoshani, Arie
Author_Institution :
Lawrence Berkeley Lab., CA, USA
fYear :
1997
fDate :
11-13 Aug 1997
Firstpage :
132
Lastpage :
143
Abstract :
The summarizability of OLAP (online analytical processing) and statistical databases is an a extremely important property, because violating this condition can lead to erroneous conclusions and decisions. In this paper, we explore the conditions for summarizability. We introduce a framework for precisely specifying the context in which statistical objects are defined. We use a three-step process to define normalized statistical objects. Using this framework, we identify three necessary conditions for summarizability. We provide specific tests for each of the conditions that can be verified either from semantic knowledge or by checking the statistical database itself. We also provide the reasoning for our belief that these three summarizability conditions are sufficient as well
Keywords :
data analysis; database theory; online operation; statistical databases; OLAP; erroneous conclusions; erroneous decisions; necessary conditions; normalized statistical objects; online analytical processing; semantic knowledge; statistical databases; statistical object definition context; sufficient conditions; summarizability; Cities and towns; Databases; Laboratories; Multidimensional systems; Terminology; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Scientific and Statistical Database Management, 1997. Proceedings., Ninth International Conference on
Conference_Location :
Olympia, WA
Print_ISBN :
0-8186-7952-2
Type :
conf
DOI :
10.1109/SSDM.1997.621175
Filename :
621175
Link To Document :
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