Palantir Technologies Inc.

Gustav Brodman

Mark Elliot

Michael Harris

Hannah Korus

Lynn Cuthriell

Brian Schimpf

Brian Toth

Jacob Meacham

Jonathan Hsiao

Michael Garland

Evelyn Nguyen

Ryan Zheng

Cody Moore

Daniel Paquette

Eric Wong

Huw Pryce

Jakub Kozlowski

Charles Post

Daniel Walker

Steven Capetta

Rick White

Alexander Feldman

Yifei Huang

Hao Dang

Yanran Lu

Yi Xue

Patricio Jones Velez

Stacey Milspaw

Patricio Velez

Techniques for secure and efficient interfacing with a cloud computing service are described. In an embodiment, a cloud computing management service is programmed or configured to communicate with a cloud computing service. The cloud computing management service can be accessed by software engineers that are looking to deploy a software instance to a computing device of the cloud computing service. Thus, the cloud computing management service acts as an intermediary layer in front of the cloud computing service. In an embodiment, the cloud computing management service may store one or more frequently-used system parameters for deployment of software instances. The parameters conform to company's security protocols, compliance protocols, and/or other standards.

Apparatus and method of securely and efficiently interfacing with a cloud computing service

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

A history preserving data pipeline computer system and method. In one aspect, the history preserving data pipeline system provides immutable and versioned datasets. Because datasets are immutable and versioned, the system makes it possible to determine the data in a dataset at a point in time in the past, even if that data is no longer in the current version of the dataset.

Universal data pipeline

History preserving data pipeline

History preserving data pipeline system and method

Growing community of inventors

Palo Alto, CA, United States of America

Gustav Brodman