Anomaly detection in data perspectives

The present invention leverages curve fitting data techniques to provide automatic detection of data anomalies in a "data tube" from a data perspective, allowing, for example, detection of data anomalies such as on-screen, drill down, and drill across data anomalies in, for example, pivot...

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Bibliographic Details
Main Author FOLTING ALLAN,THIESSON BO,HECKERMAN DAVID E.,CHICKERING DAVID M.,VIGESAA ERIC B
Format Patent
LanguageEnglish
Published 28.12.2005
Edition7
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
MEASURING
PHYSICS
TESTING
WEIGHING
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Summary:The present invention leverages curve fitting data techniques to provide automatic detection of data anomalies in a "data tube" from a data perspective, allowing, for example, detection of data anomalies such as on-screen, drill down, and drill across data anomalies in, for example, pivot tables and / or OLAP cubes. It determines if data substantially deviates from a predicted value established by a curve fitting process such as, for example, a piece-wise linear function applied to the data tube. A threshold value can also be employed by the present invention to facilitate in determining a degree of deviation necessary before a data value is considered anomalous. The threshold value can be supplied dynamically and / or statically by a system and / or a user via a user interface. Additionally, the present invention provides an indication to a user of the type and location of a detected anomaly from a top level data perspective.
Bibliography:Application Number: CN200510075848