Palantir Technologies Inc.

Matthew Lynch

Brandon Krieger

Peter Maag

Maciej Albin

Jared Newman

Mark Schafer

Jacob Albertson

Sander Kromwijk

Viktor Nordling

Mark Elliot

Greg DeArment

Jiawei Marvin Sum

Carl Freeland

Mikhail Proniushkin

Vipul Shekhawat

Jonah Scheinerman

Erin Price-Wright

Shahine Zoubeiri

Zhixian Shen

Tom O'Brien

Yanran Lu

Shaun Springer

Meghan Nayan

Giulio Mecocci

Dylan Cooke

Kyle Patron

Phillip Worton-Cross

Saad Abdali

Kevin Pyc

Timothy Dyck

Adam Borochoff

Benjamin Duffield

Punyashloka Biswal

Walker Burgin

Gregory O'Connor

Caitlin Colgrove

Matthew Sills

Stephanie Yu

Gabrielle Javitt

Nir Ackner

Alexandru Antihi

Samuel Szuflita

Diran Li

Phillip Chen

Helen Kaltegaertner

Sarun Peter Tosirisuk

Shannon Scott

Peter Tosirisuk

Maria Franco

The systems and methods described herein provide highly dynamic and interactive data analysis user interfaces which enable data analysts to quickly and efficiently explore large volume data sources. The data analysis system enables the user to investigate large volumes of data over many different paths of analysis while maintaining detailed and retraceable steps taken by the user over the course of an investigation, as captured via the user's queries and user interaction with the user interfaces provided by the data analysis system. Data analysis paths may involve exploration of high volume data sets, such as Internet proxy data, which may include trillions of rows of data. The data analyst may pursue a data analysis path that involves, among other things, applying filters, joining to other tables in a database, viewing interactive data visualizations, and so on. The data analysis system enables a user to refresh or insert a node in a workflow. The data analysis system further provides data editing, reporting, enrichment, expression language, and charting functionality.

Interactive user interface for dynamically updating data and data analysis and query processing

Example embodiments relate to a policy service employed to perform operations to: generate and maintain a data-set that comprises at least a column and a row that intersect at a cell; assign an access policy to a row or column of the data-set, wherein the access policy is defined by one or more access credentials required to receive access the cell that intersect with the row or column; receive a request to read the data-set from a user account, wherein the user account has an associated credential; filter the cell that intersects with the row or column of the data-set based on the access policy and the credential of the user account, in response to receiving the request from the user account; and provide the user account with access to the filtered data-set.

Row-level and column-level policy service

A system and methods for determining computer resource allocation, the system having a network communication interface configured to receive a query from a device, the query indicating a request to perform a processing operation on a portion of one or more data set. The system may also include data storage for data including historical information related to processing of data sets by back-end computer resources, and hardware processors configured to determine one or more scores associated with a query and based at least in part on the historical information. The system may determine a particular back-end computer resource with a highest score, provide a compute request to the particular back-end computer resource to perform a processing operation on a portion of one or more data sets, and store processing information related to the processing of the compute request by the particular back-end computer resource as historical information.

Intelligent compute request scoring and routing

Systems and methods provide a first group of computation modules configured to provide back-end compute resources for a first type of computation module by back-end compute resources. Systems and methods provide a second group of computation modules that are configured to provide back-end compute resources for a second type of computation module wherein the first and second type of computation modules are of different types. In some examples, methods and systems identify the type of computation module needed by each of a plurality of queries associated with different types of client applications based on computation module type data associated with each query and route each of the plurality of queries to an appropriate computation module within the first or second computation modules based on the computation module type data.

Systems and methods for managing queries from different types of client applications

Display screen or portion thereof with graphical user interface

Systems and methods provide a first group of computation modules configured to provide back-end compute resources for a first type of computation module by back-end compute resources. Systems and methods provide a second group of computation modules that are configured to provide back-end compute resources for a second type of computation module wherein the first and second type of computation modules are of different types. In some examples, methods and systems identify the type of computation module needed by each of a plurality of queries associated with different types of client applications based on computation module type data associated with each query and route each of the plurality of queries to an appropriate computation module within the first or second computation modules based on the computation module type data. Related methods are also disclosed.

Various systems and methods are provided that allow reviewers to review and potentially flag processed communication data in order to spot potential malfeasance or illegal activity. Certain systems and methods includes modules for removing duplicate data from the communication data files, generating thread data for email data files, generating lexicon tag data for the data files, removing blacklisted data that meets blacklisted criteria, or generating group association data.

Communication data processing architecture

Discussed herein are embodiments of methods and systems which allow engineers or administrators to create modular plugins which represent the logic for various fault detection tests that can be performed on data pipelines and shared among different software deployments. In some cases, the modular plugins each define a particular test to be executed against data received from the pipeline in addition to one or more configuration points. The configuration points represent configurable arguments, such as variables and/or functions, referenced by the instructions which implement the tests and that can be set according to the specific operation environment of the monitored pipeline.

Pluggable fault detection tests for data pipelines

Growing community of inventors

Brooklyn, NY, United States of America

Matthew Lynch