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Business Impact Analysis Using Time Correlations

  • Mehmet Sayal
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4055)

Abstract

A novel method for analyzing time-series data and extracting time-correlations (time-dependent relationships) among multiple time-series data streams is described. The application of time-correlation detection in business impact analysis (BIA) is explained on an example. The method described in this paper is the first one that can efficiently detect and report time-dependent relationships among multiple time-series data streams. Detected time-correlation rules explain how the changes in the values of one set of time-series data streams influence the values in another set of time-series data streams. Those rules can be stored digitally and fed into various data analysis tools, such as simulation, forecasting, impact analysis, etc., for further analysis of the data. Performance experiments showed that the described method is 95% accurate, and has a linear running time with respect to the amount of input data.

Keywords

Data Stream Time Correlation Change Point Processing Delay Detect Change Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Mehmet Sayal
    • 1
  1. 1.Hewlett-Packard LabsPalo AltoUSA

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