Palantir Technologies Inc.

Yifei Huang

Lawrence Manning

Rahul Kumar Agarwal

Matthew Elkherj

Daniel Erenrich

Xavier Falco

Eli Bingham

Roger Hu

Daniel Fernandez

Aleksandr Zamoshchin

Guillem Palou Visa

Rahul Mehta

Jeremy Elser

Jason Prestinario

Rowan Gilmore

Clayton Sader

Nicholas Latourette

James Edward Winchester

Grace Garde

Laurynas Pliuskys

Sarah Gershkon

Nikhita Singh

Gustav Brodman

Hao Dang

Justin Uang

Yanran Lu

Jonathan Lafleche

Yi Xue

Ovidiu-Dan Sanduleac

Onur Satici

Stacey Milspaw

Michael Xiaoxuan Yang

Andre Frederico Cavalheiro Menck

Andy Chen

Francis Chen

Nitish Kulkarni

Peter Wang

Christopher Yu

Mark Cinali

Xiangnong Wang

Ovidiu-Dan Sandulec

Computer implemented systems and methods are disclosed for automatically clustering and canonically identifying related data in various data structures. Data structures may include a plurality of records, wherein each record is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise identifying clusters of records associated with a respective entity by grouping the records into pairs, analyzing the respective pairs to determine a probability that both members of the pair relate to a common entity, and identifying a cluster of overlapping pairs to generate a collection of records relating to a common entity. Clusters may further be analyzed to determine canonical names or other properties for the respective entities by analyzing record fields and identifying similarities.

Systems and methods for automatic clustering and canonical designation of related data in various data structures

Systems, methods, and non-transitory computer readable media are provided for managing expiration of modules. An expiry dataset may be maintained. The expiry dataset may include a set of identifiers corresponding to a set of modules, a set of expiry values for the set of modules, and a set of termination tasks for the set of modules. A request to refresh a module may be received from a client. Responsive to the reception of the request, an expiry value and a termination task for the module within the expiry dataset may be updated. The expiry value may be independent of a timestamp associated with the request.

Module expiration management

Techniques for automatically scheduling builds of derived datasets in a distributed database system that supports pipelined data transformations are described herein. In an embodiment, a data processing method comprises, in association with a distributed database system that implements one or more data transformation pipelines, each of the data transformation pipelines comprising at least a first dataset, a first transformation, a second derived dataset and dataset dependency and timing metadata, detecting an arrival of a new raw dataset or new derived dataset; in response to the detecting, obtaining from the dataset dependency and timing metadata a dataset subset comprising those datasets that depend on at least the new raw dataset or new derived dataset; for each member dataset in the dataset subset, determining if the member dataset has a dependency on any other dataset that is not yet arrived, and in response to determining that the member dataset does not have a dependency on any other dataset that is not yet arrived: initiating a build of a portion of the data transformation pipeline comprising the member dataset and all other datasets on which the member dataset is dependent, without waiting for arrival of other datasets.

Dynamically performing data processing in a data pipeline system

Various systems and methods for aggregating data from disparate sources to determine an optimal package of data items are disclosed. For example, the system described herein can obtain data items from various sources, aggregate and/or organize the data items into an optimal package based on various criteria, and present, via an interactive user interface, the optimal package. Furthermore, the interactive user interface may enable a user to adjust the criteria used to aggregate and/or organize the data items. The system may interactively re-aggregate and re-organize the data items using the adjusted criteria as the user interacts with the package via the user interface. The system and user interface may thus enable the user to optimize the packages of data items based on multiple factors quickly and efficiently.

System and method for efficiently determining and displaying optimal packages of data items

Systems and user interfaces enable integration of data items from disparate sources to generate optimized packages of data items. For example, the systems described herein can obtain data items from various sources, score the data items, and present, via an interactive user interface, options for packaging the data items based on the scores. The systems may include artificial intelligence algorithms for selecting optimal combinations of data items for packaging. Further, the interactive user interfaces may enable a user to efficiently add data items to, and remove data items from, the data packages. The system may interactively re-calculate and update scores associated with the package of data items as the user interacts with the data package via the user interface. The systems and user interfaces may thus, according to various embodiments, enable the user to optimize the packages of data items based on multiple factors quickly and efficiently.

Systems and user interfaces for data analysis including artificial intelligence algorithms for generating optimized packages of data items

Growing community of inventors

Jersey City, NJ, United States of America

Yifei Huang