Palantir Technologies Inc.

Samuel Szuflita

Megha Arora

Alice Yu

Hao Dang

Nicholas Gates

Samuel Rogerson

Emily Wang

Gabrielle Javitt

Mark Elliot

Adam Borochoff

Benjamin Duffield

Punyashloka Biswal

Mark Schafer

Walker Burgin

Matthew Lynch

Caitlin Colgrove

Gregory O'Connor

Sander Kromwijk

Matthew Sills

Vipul Shekhawat

Stephanie Yu

Harsh Pandey

Nir Ackner

Brandon Krieger

Alexandru Antihi

Yeong Wei Wee

Mihir Patil

Phillip Chen

Diran Li

Helen Kaltegaertner

Satej Soman

Shannon Scott

Maria Franco

Siddharth Dhulipalla

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

A computer system is configured to receiving a data set from a data provider and automatically save the data set in a quarantine database where copying, moving, and sharing of the data set are restricted until the data set is released by a data provider. The data set is parsed to find and mark portions with potentially sensitive information. At least those parts are reviewed by a data governor, who can confirm, add, edit, or remove markers. Those parts can be visually indicated to the data governor, along with a preview of, metadata about, and analysis of the data set. After reviewing at least the automatically marked portions, the data governor can release the data set to a non-quarantine database where another user can use the data set. The user is restricted from accessing the quarantine database.

Data security

Systems and methods are provided for processing an input dataset or running an inference. The systems and methods may be configured to accept an input dataset, access one or more predefined logic plugins for processing the input dataset, process the input dataset based at least in part on a first predefined logic plugin, and generate the one or more outputs based at least in part of the processing of the input dataset. The one or more outputs may have a different format than a format of the input dataset.

Systems and methods for customizing a process of inference running

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

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New York, NY, United States of America

Samuel Szuflita