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US Patent 11314572 System and method of data alert suppression

Patent 11314572 was granted and assigned to Microsoft on April, 2022 by the United States Patent and Trademark Office.

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TimelineTable: Further ResourcesReferences
Is a
Patent
Patent
1

Patent attributes

Patent Applicant
Microsoft
Microsoft
1
Current Assignee
Microsoft
Microsoft
1
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
1
Patent Number
113145721
Patent Inventor Names
Srisaipavan Valluri1
Ayyappan Balasubramanian1
Chen Wang1
Chris Barrett1
Feng Tan1
Jon Barry Avner1
Maurizio Bruno Di Gianluca1
Date of Patent
April 26, 2022
1
Patent Application Number
172466031
Date Filed
May 1, 2021
1
Patent Citations
‌
US Patent 10534658 Real-time monitoring alert chaining, root cause analysis, and optimization
‌
US Patent 10887158 Alert dependency checking
Patent Citations Received
‌
US Patent 11550555 Dependency-based automated data restatement
Patent Primary Examiner
‌
Chae M Ko
1
CPC Code
‌
G06F 11/0751
1
‌
G06F 11/0772
1
‌
G06F 11/0778
1

A method for providing automatic suppression of an alert includes receiving a first error associated with a first dataset, the first dataset being among a plurality of datasets in a computer data environment, accessing dependency data that describes a set of dependencies between the first dataset and other datasets, examining the dependency data to automatically identify a second dataset from among the other datasets, the second dataset being a dataset on which the first dataset depends, accessing alert data for the computer data environment to determine whether an active alert for the second dataset provides an indication that the first error is redundant to a second error associated with the second dataset, and upon determining that the first error is redundant, suppressing transmission of the alert and storing data about suppressing transmission in a data structure. In determining whether the first error is redundant to the second error, timing of data generation of the first and second dataset and timing of detection of the first error are considered.

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