Platform for automated administration and monitoring of in-memory systems

    公开(公告)号:US11144383B2

    公开(公告)日:2021-10-12

    申请号:US16813934

    申请日:2020-03-10

    Applicant: SAP SE

    Abstract: Methods, systems, and computer-readable storage media for receiving, by an auto-pilot platform, one or more log files from an in-memory system, determining, by the auto-pilot platform, occurrence of a first error within the in-memory system based on the one or more logs, wherein the first error is indicated by a first error code within the one or more log files, identifying, by the auto-pilot platform, a first resolution from a resolution repository based on the first error code, the resolution repository including one or more mappings associating error codes to resolutions including associating the first error code with the first resolution, initiating, by the auto-pilot platform, execution of the first resolution, and updating, by the auto-pilot platform, the resolution repository based on execution of the first resolution.

    PLATFORM FOR AUTOMATED ADMINISTRATION AND MONITORING OF IN-MEMORY SYSTEMS

    公开(公告)号:US20210286666A1

    公开(公告)日:2021-09-16

    申请号:US16813934

    申请日:2020-03-10

    Applicant: SAP SE

    Abstract: Methods, systems, and computer-readable storage media for receiving, by an auto-pilot platform, one or more log files from an in-memory system, determining, by the auto-pilot platform, occurrence of a first error within the in-memory system based on the one or more logs, wherein the first error is indicated by a first error code within the one or more log files, identifying, by the auto-pilot platform, a first resolution from a resolution repository based on the first error code, the resolution repository including one or more mappings associating error codes to resolutions including associating the first error code with the first resolution, initiating, by the auto-pilot platform, execution of the first resolution, and updating, by the auto-pilot platform, the resolution repository based on execution of the first resolution.

    PLATFORM FOR CONVERSATION-BASED INSIGHT SEARCH IN ANALYTICS SYSTEMS

    公开(公告)号:US20210191923A1

    公开(公告)日:2021-06-24

    申请号:US16726462

    申请日:2019-12-24

    Applicant: SAP SE

    Abstract: Methods, systems, and computer-readable storage media for receiving, by a conversation-based search system (CSS) of an analytics system, verbal input from a user, providing, by the CSS, text input based on the verbal input, processing, by the CSS, the text input to determine a set of contexts, each context in the set of context representing one or more operations of an enterprise, determining, by the CSS, one or more insights based on the set of contexts, each insight representative of a performance of the enterprise, and displaying, by the analytics system, a story comprising one or more visualizations, each visualization depicting at least one insight.

    DEEP MINING OF ENTERPRISE DATA SOURCES
    4.
    发明公开

    公开(公告)号:US20240184793A1

    公开(公告)日:2024-06-06

    申请号:US18073314

    申请日:2022-12-01

    Applicant: SAP SE

    CPC classification number: G06F16/2465

    Abstract: Methods and apparatus are disclosed for deep mining of data sources. A deep miner provides extended reach into available structured databases and/or unstructured data sources. Direct evaluation of columns for relevance to a client query provides a wider array of columns having potential relevance, compared to conventional tools relying on table evaluation. Direct column evaluation is extended to unstructured data sources. A broad interface extends the reach of search seamlessly across a wide range of structured and unstructured data sources. Disclosed techniques provide superior results with reduced computing resource utilization. Limitations of human expertise are overcome. Further efficiencies are achieved through caching, ranking of columns or results, search refinement, and customized responses.

    Automatic conversion of multidimentional schema entities
    6.
    发明授权
    Automatic conversion of multidimentional schema entities 有权
    自动转换多维模式实体

    公开(公告)号:US08949291B2

    公开(公告)日:2015-02-03

    申请号:US13909139

    申请日:2013-06-04

    Applicant: SAP SE

    CPC classification number: G06F17/30292 G06F17/30914 G06Q10/0637

    Abstract: In various embodiments, a system receives a multidimensional schema entity of a first type and converts the multidimensional schema entity to a second type. The system receives user input and converts the multidimensional schema entity to the second type based on the input received from the user. In various embodiments, the system creates multidimensional schema entities automatically. In various embodiments, a method for converting multidimensional schema entities from one or more types to one or more other types is described. In various embodiments, a multidimensional schema entity is created automatically based on input from two other multidimensional schema entities. In various embodiments, two multidimensional schema entities are merged in one multidimensional schema entity. In various embodiments, multidimensional schema entities are used to generate a report. Queries extract data from the multidimensional schema entities and load it in the report. The report is presented on a graphical user interface.

    Abstract translation: 在各种实施例中,系统接收第一类型的多维模式实体,并将多维模式实体转换为第二类型。 系统接收用户输入,并且基于从用户接收的输入将多维模式实体转换为第二类型。 在各种实施例中,系统自动创建多维模式实体。 在各种实施例中,描述了将多维模式实体从一种或多种类型转换为一种或多种其他类型的方法。 在各种实施例中,基于来自两个其他多维模式实体的输入自动创建多维模式实体。 在各种实施例中,两个多维模式实体被合并在一个多维模式实体中。 在各种实施例中,多维模式实体用于生成报告。 查询从多维模式实体中提取数据,并将其加载到报表中。 该报告显示在图形用户界面上。

    Deep mining of enterprise data sources

    公开(公告)号:US12124460B2

    公开(公告)日:2024-10-22

    申请号:US18073314

    申请日:2022-12-01

    Applicant: SAP SE

    CPC classification number: G06F16/2465

    Abstract: Methods and apparatus are disclosed for deep mining of data sources. A deep miner provides extended reach into available structured databases and/or unstructured data sources. Direct evaluation of columns for relevance to a client query provides a wider array of columns having potential relevance, compared to conventional tools relying on table evaluation. Direct column evaluation is extended to unstructured data sources. A broad interface extends the reach of search seamlessly across a wide range of structured and unstructured data sources. Disclosed techniques provide superior results with reduced computing resource utilization. Limitations of human expertise are overcome. Further efficiencies are achieved through caching, ranking of columns or results, search refinement, and customized responses.

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