Palantir Technologies Inc.

Natacha Gabbamonte

Aditya Chaturvedi

Christopher Dugan

David Vogelbacher

Joseph Kane

Jiawei Wu

Benjamin Duffield

Feridun Arda Kara

Sander Kromwijk

Xinyi Wang

Vipul Shekhawat

Alexander Martino

Kamran Khan

Austin Czarnecki

Gokcan Ozakdag

Michal Adamczyk

Yixun Xu

Julien Levy

Jason Marmon

Alexander Egorenkov

Whether a logical query plan to derive a target dataset from one or more source datasets is available is determined. Responsive to determining that the logical query plan is not available for the transformation code in the first programming language, relationships between the source columns of the one or more source datasets and the respective target columns of the target dataset are inferred. Target column metadata for a target column of the target dataset is generated. The target column metadata reflects the inferred relationships between the source columns of the one or more source datasets and the respective target columns. The target column metadata for the target column of the target dataset is stored.

Column lineage and metadata propagation

Computing systems methods, and non-transitory storage media are provided for receiving a monitoring request. The monitoring request includes one or more entities or attributes to be monitored, one or more rules to be evaluated with respect to the entities or attributes, and one or more downstream actions to be selectively triggered based on the evaluation. Next, data regarding the entities or the attributes is obtained. Next, a log is generated. The log includes changes or updates, relative to a previous iteration, of the entities or the attributes. The changes or updates correspond to the rules. Next, the changes or the updates are evaluated against the one or more rules and based on the log. Next, one or more actions are selectively implemented based on the evaluation of the changes or the updates.

Monitoring and alerting mechanisms

A first computing system and methods are provided for synchronizing data with a second computing system. The computing system receives an indication of an origination of data within the first database of the first computing system. A data object that includes attributes of the originated data is generated. A first instance of the data object is incorporated into a first ontology of the first database. A second instance of the data object is transmitted to the second computing system. During the transmission, the second instance of the data object is incorporated into a second ontology of a second database within the second computing system. An update to the second instance of the data object is detected. An updated ontological representation of the updated second instance is generated, or an updated ontological representation is received from the second computing system. The updated ontological representation is incorporating into the first ontology.

Synchronization of data across different ontologies

Methods, systems, and apparatus, including computer programs encoded on computer storage media for data synchronization are provided. One of the methods includes: receiving, from a client device displaying a spreadsheet interface, a query for data; identifying, from one or more datasets in a data store, a plurality of data items responsive to the query; sending, to the client device, a plurality of data entries for display in a plurality of cells of the spreadsheet interface, wherein the data entries correspond to the identified data items; receiving, from the client device, information associated with one or more changes to one or more of the data entries, wherein the one or more changes are created based on one or more user inputs in the spreadsheet interface; and updating, in the data store based on the one or more changes, one or more of the data items corresponding to the one or more changed data entries.

Methods and systems for data synchronization

A logical query plan to derive a target dataset from one or more source datasets is identified. The logical query plan defines source columns of the one or more source datasets and respective target columns of the target dataset. The logical query plan is parsed to derive relationships between the source columns of the one or more source datasets and the respective target columns of the target dataset. Target column metadata is generated for a target column of the target dataset. The target column metadata reflects a derived relationship between one or more source columns and the target column and existing source column metadata of each of the one or more source columns. The target column metadata is stored for the target column of the target dataset.

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Natacha Gabbamonte