Machine learning enhancements to root cause analysis
AssigneeSnowflake Inc.
InventorsMichel Adar, Jay S. Tayade
Life of this patent
Estimating the term…
Abstract
Techniques described herein can monitor various data metrics. The techniques can select a subset of dimensions from a plurality of dimensions related to a data shift. The techniques including generating a plurality of decision tree graphs to classify a plurality of segments, each segment representing a combination of two or more dimensions of the subset of dimensions, and each decision tree graph including a different root node representing a respective dimension of the subset of dimensions.
Claims24
A method comprising:
- receiving a plurality of dimensions related to a data shift;
- selecting a subset of dimensions from the plurality of dimensions;
- generating, by at least one hardware processor, a plurality of decision tree graphs to classify a plurality of segments, each segment representing a combination of two or more dimensions of the subset of dimensions, and each decision tree graph including a different root node representing a respective dimension of the subset of dimensions;
- processing results of the plurality of decision tree graphs to identify contributing segments;
- and
- generating one more metrics representing contribution values of the contributing segments.
A machine-storage medium embodying instructions that, when executed by a machine, cause the machine to perform operations comprising:
- receiving a plurality of dimensions related to a data shift;
- selecting a subset of dimensions from the plurality of dimensions;
- generating, by at least one hardware processor, a plurality of decision tree graphs to classify a plurality of segments, each segment representing a combination of two or more dimensions of the subset of dimensions, and each decision tree graph including a different root node representing a respective dimension of the subset of dimensions;
- processing results of the plurality of decision tree graphs to identify contributing segments;
- and
- generating one more metrics representing contribution values of the contributing segments.
A system comprising:
- at least one hardware processor;
- and
- at least one memory storing instructions that, when executed by the at least one hardware processor, cause the at least one hardware processor to perform operations comprising:
- receiving a plurality of dimensions related to a data shift;
- selecting a subset of dimensions from the plurality of dimensions;
- generating, by at least one hardware processor, a plurality of decision tree graphs to classify a plurality of segments, each segment representing a combination of two or more dimensions of the subset of dimensions, and each decision tree graph including a different root node representing a respective dimension of the subset of dimensions;
- processing results of the plurality of decision tree graphs to identify contributing segments;
- and
- generating one more metrics representing contribution values of the contributing segments.
Dependencies are inferred from the claim text.