Autonomous aggregation identifier calculation

    公开(公告)号:US12236259B2

    公开(公告)日:2025-02-25

    申请号:US17522585

    申请日:2021-11-09

    Applicant: STRIPE, INC.

    Abstract: The subject technology performs a transaction locally at a computing node. The subject technology determines that the transaction has been completed. The subject technology determines a set of immutable attributes from the completed transaction. The subject technology generates an aggregate identifier based on the set of immutable attributes. The subject technology publishes the generated aggregate ID. The subject technology stores the published aggregate ID to an external storage location.

    DATABASE ANOMALY DETECTION
    2.
    发明公开

    公开(公告)号:US20230214379A1

    公开(公告)日:2023-07-06

    申请号:US17566014

    申请日:2021-12-30

    Applicant: STRIPE, INC.

    CPC classification number: G06F16/2365 G06F16/2379

    Abstract: In one aspect, a method of detecting database anomalies, includes reading historical data in a destination database at an end of a data pipeline, determining bounds including an upper bound and a lower bound based on the read historical data, reading current data for a first specified time period in the destination database, responsive to determining the upper or the lower bound is exceeded, determining database transactions that caused the exceeding, and transmitting alerts to owners of the database transactions.

    BOTS FOR ACCOUNTING
    3.
    发明申请

    公开(公告)号:US20240411758A1

    公开(公告)日:2024-12-12

    申请号:US18208002

    申请日:2023-06-09

    Applicant: STRIPE, INC.

    Abstract: Aspects of the present disclosure relate to systems and methods for generating processes or bots for automatically processing accounting data. Some aspects of embodiments relate to defining templates specifying actions to be performed on a periodic basis (e.g., hourly, daily, weekly, or monthly). In some embodiments, the templates further include template queries for querying data stores or other data sources (e.g., data streams). The templates may be registered for scheduled execution, instantiating the templates with runtime parameters for execution, where executing the instantiated templates includes collecting and processing data collected from source data stores to generate output data. Some aspects relate to temporarily storing output data generated by executing the instantiated templates and requesting manual approval of the output data before the data is written to an output data store or sink data store. In some circumstances, the output data store may store a general ledger of a business.

    Database anomaly detection
    4.
    发明授权

    公开(公告)号:US11995065B2

    公开(公告)日:2024-05-28

    申请号:US17566014

    申请日:2021-12-30

    Applicant: STRIPE, INC.

    CPC classification number: G06F16/2365 G06F16/2379

    Abstract: In one aspect, a method of detecting database anomalies, includes reading historical data in a destination database at an end of a data pipeline, determining bounds including an upper bound and a lower bound based on the read historical data, reading current data for a first specified time period in the destination database, responsive to determining the upper or the lower bound is exceeded, determining database transactions that caused the exceeding, and transmitting alerts to owners of the database transactions.

    AUTONOMOUS AGGREGATION IDENTIFIER CALCULATION

    公开(公告)号:US20230145485A1

    公开(公告)日:2023-05-11

    申请号:US17522585

    申请日:2021-11-09

    Applicant: STRIPE, INC.

    CPC classification number: G06F9/466 G06Q10/067

    Abstract: The subject technology performs a transaction locally at a computing node. The subject technology determines that the transaction has been completed. The subject technology determines a set of immutable attributes from the completed transaction. The subject technology generates an aggregate identifier based on the set of immutable attributes. The subject technology publishes the generated aggregate ID. The subject technology stores the published aggregate ID to an external storage location.

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