Palantir Technologies Inc.

Cornell Research Foundation Inc.

Jonathan Victor

Anshuman Prasad

Casey Patton

Arjun Mathur

Lucas Lemanowicz

John McRaven

Mikhail Proniushkin

Geoffrey Stowe

Andrew Pettit

Joy Tao

Nabeel Qureshi

Benedict Cappellacci

Ankit Shankar

Rahij Ramsharan

Thomas Mathew

Andrew Ash

Mitchell Skiles

Andy Chen

Sri Krishna Vempati

Christopher Wynnyk

Samuel Sinensky

Joanna Peller

Nikhil Taneja

Scott Adams

Christopher Rogers

Ryan Norris

Anuraag Bahl

Vinoo Ganesh

Aydin Keskin

Mackenzie Bohannon

Nicholas D Schiff

Michael Repucci

A system and method for processing data wherein one or more user selections of source data and an input defining one or more operations to be performed on the selected source data are received to generate processed data for display as a chart; the source data is retrieved from at least one data source, the source data is processed according to the defined one or more operations to generate processed data for output for display as a chart, the chart is stored as data defining the one or more operations and data identifying the source data operated on, a further user selection is received to redisplay the chart; retrieving the source data from the at least one data source; and the source data is processed according to the defined one or more operations to generate the processed data for output for redisplay as the chart.

Systems and methods for retrieving and processing data for display

A system for troubleshooting network problems is disclosed. A model can use demographic information, network usage information, and network membership information to determine an importance of a problem. The importance of the problem for the user who reported the problem, a number of other users affected by the problem, and the importance of the problem to the other users can be used to determine a priority for resolving the problem. Before and after a work order is executed to resolve the problem, network metrics can be gathered, including aggregate network metrics, and automatically presented in various user interfaces. The analysis of the metrics can be used to update a database of which work orders are assigned in response to which problems.

Computer network troubleshooting

A canonical decomposition (CD) method that includes building a multi-variate linear autoregressive ('MLAR') model from an original data set or from a reduced set derived by data reduction methods from the original data set. The MLAR analysis is followed by seeking a coordinate transformation of the MLAR model to obtain the best possible match with one or more canonical forms representing relationships among components. For multi-variate data with a truly hierarchical structure, CD accurately extracts the underlying sources of the system.

Method and system for analyzing multi-variate data using canonical decomposition

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New York, NY, United States of America

Jonathan Victor