Palantir Technologies Inc.

Gabrielle Javitt

Caitlin Colgrove

Mark Schafer

Walker Burgin

Helen Kaltegaertner

John Antonio Carrino

Bianca Rahill-Marier

Andrew Moreland

Jacob Sanches

Alexander Taheri

Xiaohan Zhang

Joshua Chomicki

Benjamin Hamme

Dzmitry Dulko

Josh Munsch

Paul Ryan

Harsh Pandey

Samuel Szuflita

Adil Majid

Mark Elliot

Adam Borochoff

Benjamin Duffield

Lucas Ray

Mitchell Beard

Punyashloka Biswal

Stephen Yazicioglu

Matthew Lynch

Gregory O'Connor

Matthew Sills

Sander Kromwijk

Vipul Shekhawat

Stephanie Yu

Alexandru Antihi

Brandon Krieger

Nir Ackner

Kendra Knittel

Phillip Chen

Diran Li

Satej Soman

Shannon Scott

Evan Brown

Douglas Proctor

Andrew Buie

Hunter Wills

Claire Dolin

Maria Franco

Siddharth Dhulipalla

Display screen or portion thereof with graphical user interface

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

Systems and methods are provided for obtaining sensor data comprising one or more entities and one or more attributes of the respective one or more entities. The systems and methods may be configured to infer one or more relationships between the respective one or more entities based on the one or more attributes, and update the sensor data based on the inferred one or more relationships.

Systems and methods for inferring relationships between entities

Systems and methods are provided for generating reports reflecting a visualization of, e.g., a dataset on which data analysis has been performed. The data analysis performed on the dataset may be an aggregation of data analysis functionality provided by applications or tools. Dataset visualization is realized in a workspace implemented by a separate application or tool. Potential conflicts regarding updating one or more elements of the dataset are reconciled by implementing a dual operational transform system and method. A global state of the dataset may be determined by a first operational transform system and method, while a local state of the dataset may be determined by a second operational transform system and method. The local state of the dataset may be updated through operational transforms exchanged between the first and second operational transform systems that align the local state of the dataset with the global state of the dataset.

Systems and methods for data analysis and visualization and managing data conflicts

Disclosed herein are systems and methods for joining datasets. The system may include one or more processors and a memory storing instructions that, when executed by the one or more processors. The processor may cause the system to perform determining at least a first database table to be annotated, the first database table including a set of columns and rows of a dataset. In some embodiments, the system may include determining at least one typeclass that applies to one or more columns included in the first database table, wherein the typeclass describes values stored in the one or more columns and annotating the one or more columns, wherein the annotated columns are associated with the typeclass.

Systems and methods for annotating datasets

A first dataset from one or more databases and a second dataset from the one or more databases may be identified. The first dataset may contain first data while the second dataset may contain second data. A first relationship measure may be computed for the first dataset, where the first relationship measure is configured to represent the first data in a first condensed format. A second relationship measure may be computed for the second dataset, where the second relationship measure is configured to represent the second data in a second condensed format. A join key may be computed using the first relationship measure and the second relationship measure. The join key may represent a correspondence area between the first dataset and the second dataset. An interactive user interface element may be configured to display a graphical depiction of the correspondence area between the first dataset and the second dataset.

Systems and methods for determining relationships between datasets

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New York, NY, United States of America

Gabrielle Javitt