Abstract: According to an aspect of some embodiments of the present invention there is provided a computer implemented method for detecting at least one anomaly in a dataset, comprising: managing a dataset including a plurality of data entities each including at least one value; receiving a semantic model that defines associations between two or more data entities; forming a plurality of multi dimensional data instances, each multi dimensional data instance formed from at least one of a permutation and a combination of a set of data entities from the plurality of data entities according to the semantic model; analyzing the multi dimensional data instances to detect at least one anomalous value, the anomalous value representing a statistically significant deviation according to a deviation requirement, of one or more values from a set of values of the multi dimensional data instances; and providing the detected at least one anomalous value.

Abstract: According to an aspect of some embodiments of the present invention there is provided a computer implemented method for detecting at least one anomaly in a dataset, comprising: managing a dataset including a plurality of data entities each including at least one value; receiving a semantic model that defines associations between two or more data entities; forming a plurality of multi dimensional data instances, each multi dimensional data instance formed from at least one of a permutation and a combination of a set of data entities from the plurality of data entities according to the semantic model; analyzing the multi dimensional data instances to detect at least one anomalous value, the anomalous value representing a statistically significant deviation according to a deviation requirement, of one or more values from a set of values of the multi dimensional data instances; and providing the detected at least one anomalous value.