Microsoft Technology Licensing, LLC

Salesforce Com, Inc.

Zeqiang Wang

Roman Batoukov

Khoa Van Tran

Suren Aghajanyan

Keiji Kanazawa

Sai Sankalp Arrabolu

Jian Zhang

Benjamin J Lofton

Richard Wydrowski

Lech Gudalewicz

Thomas W Potthast

Ana Bertran

Gautham Ramachandran

Gerald Gibson, Jr

Michael Elizarov

Systems and methods for data anomaly detection include recommending one or more algorithms from a set of algorithms to process received time series data, wherein the one or more algorithms are recommended based at least in part on a type of workload for processing the received time series data. Assisted parameter tuning is provided for a detected anomaly alert and calibration, and the received time series data is processed based on a user selected algorithm that is parameter tuned.

Data anomaly detection

A method of data processing includes identifying a segment of entity identifiers that are associated with a target tenant and correspond to a set of clients that are to receive at least one content object via a first channel of a plurality of supported channels. The method includes modifying a feature associated with communication of content for a test subset of the segment relative to a control subset of the segment, determining a first metric corresponding to the control subset and the test subset in association with the communication of the content via the first channel and a second metric associated with the target tenant over a second channel of the plurality of channels. The method includes comparing the second metric to a metric associated with a peer group of tenants, and adjusting subsequent communications for the target based at least in part on the comparing and the first metric.

Scalable multi-channel content distribution and optimization using peer comparison

Growing community of inventors

Redmond, WA, United States of America

Zeqiang Wang